{"as_of":"2026-08-19T21:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e47ee9995a2462bab0e287b14e8f36c06587cc41991c7a9353a8bdde8aa3a762","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T19:39:55.643559Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.09900/citation-record","integrity":"/paper/2501.09900/integrity","json":"/paper/2501.09900/citation-record.json","paper":"/paper/2501.09900"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.412948Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.412948Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:4169a5faf7eeb044122fe7d22f99748aaa3b0ce70b09c91647ffca2d37819e36","observation_id":"061b3630-94ad-4aad-b600-f8cba400e16e","resolution":{"observed_at":"2026-08-10T19:39:55.412948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.419707Z","title":"Bart: Bayesian additive regression trees","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.419707Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:9b2cf5abba6d004b3dda67e7c94a620d7a7a36910b8769405de9e2031c8f2a60","observation_id":"0186d0ef-66f9-4f11-b9c2-b9481ae35a6f","resolution":{"observed_at":"2026-08-10T19:39:55.419707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.425395Z","title":"A decision-theoretic generalization of on-line learning and an application to boosting","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.425395Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:5b30548b87b8dee1c2fae1830589dc7029148ed1098f2eebdb41db2f33cd1de6","observation_id":"6b1ce61c-d341-439b-87e7-6d5c89057831","resolution":{"observed_at":"2026-08-10T19:39:55.425395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.430954Z","title":"Bagging predictors","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.430954Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:1e3f4fc03c6351da89ba9c3abf3eed3937d669e8ccf1c6b2e5c130c8218e0f72","observation_id":"2620c516-1157-4f26-b61f-cac0d718c691","resolution":{"observed_at":"2026-08-10T19:39:55.430954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.437463Z","title":"Random forests","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.437463Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:a2f854c8e9f980bad70ad63d577773595956fbd8fa950617e75b59f3dae1ad89","observation_id":"66f1a42d-617b-4fee-a908-477f66300d4c","resolution":{"observed_at":"2026-08-10T19:39:55.437463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.403157Z","title":"The B ayesian additive classification tree applied to credit risk modelling","venue":null,"work_id":"5c323ab5-2a98-4f02-9da8-aaaec95dd320","year":2010},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.443031Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:7a759f1c89991e7d0acdd353cde98916c0763ba3fe9b8c7228a2a1309e1d89f1","observation_id":"0f6f0f9f-f088-4ee8-903a-1e129b64bb1a","resolution":{"observed_at":"2026-08-10T19:39:56.408724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.385268Z","title":"Multinomial probit B ayesian additive regression trees","venue":null,"work_id":"a815d335-2a38-4930-bd8b-4dbc0f018afc","year":2016},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.448366Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:32319cdc73e6b1739307fe7d87d34d472eaf5b01e11a68f3a3ccf56c3170b66c","observation_id":"8074f6a7-cdab-4097-92a6-d7cebdbc78dc","resolution":{"observed_at":"2026-08-10T19:39:56.391318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.369147Z","title":"Variable selection for BART : an application to gene regulation","venue":null,"work_id":"337f724b-c38e-4fef-9db2-fdb693ecb524","year":2014},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.454199Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:75d81c3c0ed5936c95c64026387f3e752e6fe3974fd6176add514a23fad2a8ac","observation_id":"e1a9cfc3-f48d-4c36-abbd-79e1f6321783","resolution":{"observed_at":"2026-08-10T19:39:56.374131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.352649Z","title":"Bayesian regression trees for high-dimensional prediction and variable selection","venue":null,"work_id":"f8e53fdd-61bb-439a-bd5b-05efd61218af","year":2018},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.459524Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:90c5ed398fa7eefd84b9063a962ac7647389faf0caee1d02722a510abe368ea8","observation_id":"e56c2036-cf91-4cc0-af41-66135548a528","resolution":{"observed_at":"2026-08-10T19:39:56.358378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.335909Z","title":"m BART : M ultidimensional M onotone BART","venue":null,"work_id":"31bff41d-ac64-4f4f-96c4-f370e9cc3ebd","year":2021},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.464777Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:88142550c8f973ab4c88f1e1f200ca4746af6bc9c56bc556469acb35be901173","observation_id":"e0795f0e-ba10-4b1c-a1b5-ebc9cec1e71a","resolution":{"observed_at":"2026-08-10T19:39:56.341244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.469778Z","title":"Bayesian nonparametric modeling for causal inference","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.469778Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:fe654a44ea9d3aa772cf8ccb8d22f5960b3cbbd997aa177d3ee1ee9114cb2d9a","observation_id":"b0fdbf7e-bc5d-4abd-ba20-50c3288a0cb0","resolution":{"observed_at":"2026-08-10T19:39:55.469778Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.304432Z","title":"Nonparametric survival analysis using B ayesian additive regression trees ( BART )","venue":null,"work_id":"7c0abfbc-bdd3-46fc-a0b3-f3bf8539624c","year":2016},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.474838Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:f8d736c9baabcc4455d7148dff3b2ec6c87454279f66933af530ced133daeb1b","observation_id":"9bd2af00-7c55-47fa-ace2-91911d70dfc2","resolution":{"observed_at":"2026-08-10T19:39:56.311290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1402.5397","last_updated":"2014-02-21T19:58:59Z","snapshot_observed_at":"2026-08-15T16:55:42.224944Z","submitted_at":"2014-02-21T19:58:59Z","title":"Bayesian Additive Regression Trees With Parametric Models of Heteroskedasticity","version":1},"cited_work":{"arxiv_id":"1402.5397","doi":null,"metadata_source":"pith","pith_arxiv_id":"1402.5397","snapshot_observed_at":"2026-08-10T19:39:55.848950Z","title":"Bayesian Additive Regression Trees With Parametric Models of Heteroskedasticity","venue":"stat.ME","work_id":"4e39c944-7fcf-433b-9cd2-d8399eb3cfd1","year":2014},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.480258Z"},"links":{"cited_paper":"/paper/1402.5397","citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:822bf46e954f48ad59b195c73c6e6386df653bcadfc0d785993a1ceb6a0b5196","observation_id":"3fe99e3c-a92b-4ed6-a50a-3f503a1954be","resolution":{"observed_at":"2026-08-10T19:39:55.855441Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.286304Z","title":"Efficient M etropolis-- H astings proposal mechanisms for B ayesian regression tree models","venue":null,"work_id":"ec73fa20-cf59-4462-b05e-803d5a7a2eff","year":2016},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.486452Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:c7b4b62fa1a615a17f71f8258c5bfd41c0141cdfb10e092a60983db7df484d3a","observation_id":"61394d8a-bbaf-4577-8cea-9a3e1ee36140","resolution":{"observed_at":"2026-08-10T19:39:56.291778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.269288Z","title":"Log-linear B ayesian additive regression trees for multinomial logistic and count regression models","venue":null,"work_id":"cf7a3b13-375a-4171-98a1-a6c77a6db3dd","year":2021},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.493268Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:b839b9c651522acd68135b811267e98fbbc1e18465ec43947483aaeb22fe7e81","observation_id":"7ed83fd9-b578-4d85-aca6-9dcf13e27003","resolution":{"observed_at":"2026-08-10T19:39:56.274627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.252525Z","title":"Bart-based inference for poisson processes","venue":null,"work_id":"254ce1af-2af3-4bfe-a717-b2a344c4b1b9","year":2023},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.499619Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:e7effe522fcdc7adc20bf4bc2f44221c23c5e13954c0a8a1a56faf508fb0efb4","observation_id":"f9551f7f-aa46-4356-888e-08f4db9c9e80","resolution":{"observed_at":"2026-08-10T19:39:56.257599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.235405Z","title":"Posterior concentration for B ayesian regression trees and forests","venue":null,"work_id":"b3b37876-c0ad-44c1-9a18-cbb52e3c1cc9","year":2020},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.505138Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:85c551844f9f3d231540f5a7d07515ea56f7ef6cf0668d84a71b95078860f782","observation_id":"54d7bd5a-15bc-4b98-9fef-8d5aed508fb8","resolution":{"observed_at":"2026-08-10T19:39:56.241086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.217593Z","title":"On T heory for BART","venue":null,"work_id":"ed1e9602-515b-4b1e-8cb7-f182c86b12f7","year":2019},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.510524Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:281e1bf69b1c3f52da31161a18275eefa9a077991926c135f935259142726c5f","observation_id":"36032fab-ca58-47c6-85f2-f7d9b5563526","resolution":{"observed_at":"2026-08-10T19:39:56.223469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.200386Z","title":"Bayesian regression tree ensembles that adapt to smoothness and sparsity","venue":null,"work_id":"e98c349f-3020-4372-83e4-b6aa8d09b8a9","year":2018},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.515769Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:f9c6fe275db9b5b7582a08c62404b862e6c1585e03f85133d75eeb90a46acdd9","observation_id":"e9141b54-d34a-40a6-8256-dd8bc44baef2","resolution":{"observed_at":"2026-08-10T19:39:56.205803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.182139Z","title":"Random tessellation forests","venue":null,"work_id":"58906575-2404-4810-8799-7eef97867600","year":2019},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.520840Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:ca5aecb4e05e622b971248b2ebbccbf79c16cae6a71a2a3599f09835c1740e6f","observation_id":"a6e26753-ff9b-4d97-bc45-fc3e7a66ae74","resolution":{"observed_at":"2026-08-10T19:39:56.187305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.165880Z","title":"The Ostomachion Process","venue":null,"work_id":"14fe0c93-685f-4c26-9450-7272f322f6d0","year":2016},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.526354Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:8baaaef9aa01ffd8059ddb93186801bf8240d885e091fbfb0b1d90c23af26267","observation_id":"339625a6-4927-4022-bd0f-a1cdf15c6d0f","resolution":{"observed_at":"2026-08-10T19:39:56.170760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.148457Z","title":"Sparse projection oblique randomer forests","venue":null,"work_id":"1f58ce69-5809-4f63-be42-b3a6baede858","year":2020},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.531369Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:5f23882aa8bcc03bd1e75a74d075b0744e4b1ac89671793a54dcb11b58b3004d","observation_id":"d807d7f6-bba2-4a3b-b896-7b63d0fe2e48","resolution":{"observed_at":"2026-08-10T19:39:56.154226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1507.05444","last_updated":"2017-08-09T16:55:56Z","snapshot_observed_at":"2026-08-14T22:39:47.513174Z","submitted_at":"2015-07-20T10:51:02Z","title":"Canonical Correlation Forests","version":6},"cited_work":{"arxiv_id":"1507.05444","doi":null,"metadata_source":"pith","pith_arxiv_id":"1507.05444","snapshot_observed_at":"2026-08-10T19:39:55.822686Z","title":"Canonical Correlation Forests","venue":"stat.ML","work_id":"c0cc1272-1297-439b-b2c1-c89077dd7d35","year":2015},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.536365Z"},"links":{"cited_paper":"/paper/1507.05444","citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:abd69aa98a9f7969032ea42cb2d7a12674e56ae7de44ef2492df4000c83e61f5","observation_id":"2df9cc43-beaa-42a0-95cd-b53bdd6afdfb","resolution":{"observed_at":"2026-08-10T19:39:55.829003Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.130172Z","title":"Rotation forest: A new classifier ensemble method","venue":null,"work_id":"d18f29f5-cf51-44d0-8e2c-7ae259f807ba","year":2006},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.542606Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:f2a08be28fe9ee8dc9c5a41524fcc97232683bad656e0d7c3916ee23276aea9d","observation_id":"550627db-825c-42a4-8257-6890f11136b4","resolution":{"observed_at":"2026-08-10T19:39:56.135740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.113078Z","title":"Regularizing axis-aligned ensembles via data rotations that favor simpler learners","venue":null,"work_id":"f151e19b-a1b6-43a9-81d2-17e5b9696869","year":2021},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.548602Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:1eb6bb20ba26a4f6536d64df64acb81b7dfe9e348813a32f71360c41764d65d9","observation_id":"85891284-5c9a-43ca-aa37-cea758864b91","resolution":{"observed_at":"2026-08-10T19:39:56.118417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.096206Z","title":"Random rotation ensembles","venue":null,"work_id":"14de1347-aea3-4bb8-bbe3-8afe55ffb8fc","year":2016},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.554215Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:87ae6b33d0950882028b2739d37cc4172fadd5f04f77329cb9f88c7a103a7048","observation_id":"40aac431-445e-4230-85c4-c9fe6527bb3e","resolution":{"observed_at":"2026-08-10T19:39:56.101329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.078390Z","title":"Addivortes:(bayesian) additive voronoi tessellations","venue":null,"work_id":"a5338f9c-17f6-45c7-8df4-52a1285b34af","year":2024},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.559653Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:8d36aecd8a1c88e9f4ed3462eaf2cdf11010cebb90b5614ee6fd5a25920aedc1","observation_id":"a55a248f-d39c-4026-8929-751c95656bd4","resolution":{"observed_at":"2026-08-10T19:39:56.084794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.10785","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.790216Z","title":null,"venue":null,"work_id":"a59e023f-fcb0-4e24-a0df-121d9d59395f","year":2024},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.565707Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:3b26d93f0502cb9d095fb3e8e949e7bc0cd5054f2945fd78f51531c348a3e628","observation_id":"c501f434-6fcd-4d07-bb3d-403b4a64c73e","resolution":{"observed_at":"2026-08-10T19:39:55.800601Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.060938Z","title":"Bamdt: Bayesian additive semi-multivariate decision trees for nonparametric regression","venue":null,"work_id":"74fdc701-d92b-4d47-8b48-ec5adc3ed2d5","year":2022},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.571745Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:6ce31e6ad702c3cc7acff6460d970d9934d3d8285cd790f62be4d9fde32d330c","observation_id":"f6a6cc00-4951-413f-8891-56d6ef220ef8","resolution":{"observed_at":"2026-08-10T19:39:56.066779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.10430","last_updated":"2020-07-20T19:41:41Z","snapshot_observed_at":"2026-08-19T15:00:12.218053Z","submitted_at":"2020-07-20T19:41:41Z","title":"A Survey of Algorithms for Geodesic Paths and Distances","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.10430","snapshot_observed_at":"2026-08-10T19:39:55.579376Z","title":"A survey of algorithms for geodesic paths and distances","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.579376Z"},"links":{"cited_paper":"/paper/2007.10430","citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:829ea9effc670805c66b3c1717c9263b2b29c5a8a57a0c0b6e23f26bbb80f752","observation_id":"75fd21f6-c2de-4016-ba15-2b1ffd7957f3","resolution":{"observed_at":"2026-08-10T19:39:55.579376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.585487Z","title":"Normalized cuts and image segmentation","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.585487Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:b87bac87f3c17d795a701922e1c14bd3dd0496479cf77c72372a28ecec1139fe","observation_id":"79aa53d9-02b9-4122-a561-cd5fb433a8b5","resolution":{"observed_at":"2026-08-10T19:39:55.585487Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.590532Z","title":"Diffusion maps","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.590532Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:b45663224fb43b926f6631f95507f05e0a336cbd8b415bef529ba21ea91a9fa7","observation_id":"eb31ca31-61eb-400e-83d2-1a7825c78768","resolution":{"observed_at":"2026-08-10T19:39:55.590532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.595783Z","title":"Laplacian eigenmaps for dimensionality reduction and data representation","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.595783Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:d4bb37a05c92da6a7bf986e25fec2d55ea6b451149bbe86a1f386491466173e8","observation_id":"fb6bea04-4488-4576-aa77-7f75056eab31","resolution":{"observed_at":"2026-08-10T19:39:55.595783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:56.008298Z","title":"Random walks on graphs","venue":null,"work_id":"6a341a9f-4571-4625-9fd9-b98af865e716","year":1974},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.600834Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:7f5e6c5692b6492e069cad175ba3eeb3c6b978cccee9dd6f48acc823d0065648","observation_id":"a653d1eb-cea8-4d0c-b495-864dbd777b01","resolution":{"observed_at":"2026-08-10T19:39:56.013531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.988513Z","title":"Graph based gaussian processes on restricted domains","venue":null,"work_id":"9715b3a1-a1fd-4bb4-8623-beb29360122e","year":2022},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.606135Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:46b305b87241f686a1612483c8019bd39855e161f27fb95e128ecd656eae39ef","observation_id":"5d017a8d-a5b9-47de-b3c1-562e082ef5db","resolution":{"observed_at":"2026-08-10T19:39:55.994614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.969509Z","title":"Understanding predictive information criteria for bayesian models","venue":null,"work_id":"ba843c15-ae3d-46ce-abb3-cc129f76b6f1","year":2014},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.611179Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:9c4a373c525db573019d24815255c5dd363aaa248905dd4a6dd49715f9ff1ce0","observation_id":"fdda0a67-26fe-4b42-a9d3-c23bb3b8c7f6","resolution":{"observed_at":"2026-08-10T19:39:55.975548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.951482Z","title":"Stochastic tree ensembles for regularized nonlinear regression","venue":null,"work_id":"861542a0-5520-43dc-8612-64488f9d1e18","year":2023},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.616717Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:d70af2cd080e79aeb6edfb70172048c48063d24c635bc7623534862c2ca5d5ef","observation_id":"7d3f1bf0-3a44-4161-9986-95393fb2ad5f","resolution":{"observed_at":"2026-08-10T19:39:55.957586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.934022Z","title":"The theory of branching processes, volume 6","venue":null,"work_id":"d6899dd6-e804-4e74-9640-e6174ee1113f","year":1963},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.622636Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:f88c2e220621d08ca30fb1f53f1743f9ca3cd5b80964768ac268ddfb5e8aad9d","observation_id":"45b94d60-79c4-4ce2-864b-b9a6f91f93bf","resolution":{"observed_at":"2026-08-10T19:39:55.939506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.916864Z","title":"Local gaussian process extrapolation for bart models with applications to causal inference","venue":null,"work_id":"d8aa51b0-bf78-4ad0-8bf0-3ad3b0d719fc","year":2024},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.627827Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:2c3af6f6109f7697420f8c5300f8cfd364fb51c753ed8551718a9f3fa470f5d5","observation_id":"317014d7-223f-4fa4-b56f-6c5877ec98aa","resolution":{"observed_at":"2026-08-10T19:39:55.922184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.898697Z","title":"B ayesian backfitting (with comments and a rejoinder by the authors)","venue":null,"work_id":"3e46330a-b259-41d4-94d8-67cd674f7301","year":2000},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.633057Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:f9e1d8e93d70581c2270ccfd60ceb51a3c7354b70a4bd2fc12433793dce8d4d5","observation_id":"2a00a7c2-7a71-4ac7-826e-1a9396f5e569","resolution":{"observed_at":"2026-08-10T19:39:55.904095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.638455Z","title":"Strictly proper scoring rules, prediction, and estimation","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.638455Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:2c36e321f15f9e276951e68f236ea5fc087a2a31d7f75e1ee9a58e93c9fec2cd","observation_id":"3db0d765-c4c8-4b3d-bf61-d63944ea8626","resolution":{"observed_at":"2026-08-10T19:39:55.638455Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:39:55.867697Z","title":"URL :https://geodacenter.github.io/data-and-lab/NYC_Tract_ACS2008_12/","venue":null,"work_id":"1a5d17f7-a2ce-4c4c-ae0f-3d5f28bf7818","year":null},"citing_paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-10T19:39:55.643559Z"},"links":{"citing_paper":"/paper/2501.09900"},"observation_digest":"sha256:8304c516b879729193bc4cb731e40a064fe04fc99a9f5d0189996dad443eed49","observation_id":"5810e8e2-9736-4871-af12-8290814447c5","resolution":{"observed_at":"2026-08-10T19:39:55.873349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.09900","last_updated":"2025-01-17T01:13:44Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-17T02:34:17.992578Z","submitted_at":"2025-01-17T01:13:44Z","title":"SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":11,"verified_exact":2,"verified_fuzzy":28},"total_outbound_references":42},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2501.09900."}