{"as_of":"2026-08-10T23:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0ba59bc50c458389607c53fafe76687b08db6a4ae84fd626d0452030f3735919","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:34:01.816574Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2507.05510/citation-record","integrity":"/paper/2507.05510/integrity","json":"/paper/2507.05510/citation-record.json","paper":"/paper/2507.05510"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:33:59.286114Z","title":null,"venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.286114Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:32d3942d559fd6527a24a653165d3e7d501776f62246df2267cd8a723203a5a9","observation_id":"2689d7d2-8779-43b8-9ec1-e26c42649051","resolution":{"observed_at":"2026-08-06T19:33:59.286114Z","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":"2026-08-06T19:33:59.340395Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.340395Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:4ccd93daef326e4303b90e41c92bd66209b84c263bf945c9899af380664b358f","observation_id":"08ea814b-7077-4a66-9651-1809ec385118","resolution":{"observed_at":"2026-08-06T19:33:59.340395Z","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":"2026-08-06T19:33:59.393483Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.393483Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:a9f2ccd61dd7ae82b33a0b5fa385a5ede8dd9f2b0842689085d83e905260591c","observation_id":"9b79fb8b-48cc-433c-a4ab-dc335887394f","resolution":{"observed_at":"2026-08-06T19:33:59.393483Z","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":"2026-08-06T19:33:59.433087Z","title":null,"venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.433087Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:aae7f5730120b18116a33779b1885832422c27372f0114f99deeb68ba4ea9c39","observation_id":"bf2e7c83-845f-40fe-a413-1997a38e409e","resolution":{"observed_at":"2026-08-06T19:33:59.433087Z","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":"2026-08-06T19:33:59.494575Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.494575Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:0ed7146ff76661891a68268339b684bab41fe075c7d2677d525406b04ff67a97","observation_id":"47a9ed73-8195-4ac1-8854-0ace93ae80df","resolution":{"observed_at":"2026-08-06T19:33:59.494575Z","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":"2026-08-06T19:33:59.553868Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.553868Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:79586374d996b860bdc4abc1c1ea0605bb59a24308f621bddeceb89f2c11228d","observation_id":"955ad1da-96fe-45c9-a059-3503d8c7db51","resolution":{"observed_at":"2026-08-06T19:33:59.553868Z","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":"2026-08-06T19:33:59.628545Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.628545Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:3f6848b5db3a6508ebf680fce8919cedf5690f80f0cc6927a775ddcb137928a9","observation_id":"a3466bc1-a0bc-4f05-bcd6-69e9e3dde368","resolution":{"observed_at":"2026-08-06T19:33:59.628545Z","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":"2026-08-06T19:33:59.678016Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.678016Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:484774c2206be3cc2ce002e65be66d5d342cad961de9beefbf31a3bbdcdb2a9b","observation_id":"fed511fe-61f8-4fe4-af53-61595d6a53d0","resolution":{"observed_at":"2026-08-06T19:33:59.678016Z","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":"2026-08-06T19:33:59.751655Z","title":"Hanna, Scott D","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.751655Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:674b5715974f779172351e9b59e6f535efa331bf0385399ea779c8aee0747804","observation_id":"b43dc771-02f9-4e12-98d7-d357167cb293","resolution":{"observed_at":"2026-08-06T19:33:59.751655Z","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":"2026-08-06T19:33:59.827937Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.827937Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:3345b58eeb3182575ea883f4d9613965ea56aef1d9d72c93a78a557ac0c6e122","observation_id":"fe75b161-f9fc-49f0-a9c6-ece32f14a5eb","resolution":{"observed_at":"2026-08-06T19:33:59.827937Z","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":"2026-08-06T19:33:59.883914Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.883914Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:41d6b1ddc570c4be25c867d8088ae7319415fc5bd8083ac274f3788d208c44a3","observation_id":"1fbb099d-48c6-46f8-b2b6-60a93da7c43f","resolution":{"observed_at":"2026-08-06T19:33:59.883914Z","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":"2026-08-06T19:34:03.157739Z","title":null,"venue":null,"work_id":"c29b0549-6847-43c3-b2c7-3aa3bd318777","year":2018},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:33:59.969246Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:5d2294f9025076a1a1a68279ff01b5307f99c3aed51ea94bfdcce2a636ec5ecf","observation_id":"f4217118-7e6c-4082-8458-16e1345508e1","resolution":{"observed_at":"2026-08-06T19:34:03.205859Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:02.954472Z","title":null,"venue":null,"work_id":"98b9a3f3-b860-4361-9fba-6fa1c8a09df5","year":1987},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.053346Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:311266b8e6cfc0848b6f77589972f59ccdd45fb7dbfe008bc763dd1e2a8f3280","observation_id":"8455a77a-8d33-4850-9f39-af8ada26b6d0","resolution":{"observed_at":"2026-08-06T19:34:03.076162Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03461","last_updated":"2019-04-24T03:01:02Z","snapshot_observed_at":"2026-07-06T05:46:24.221340Z","submitted_at":"2017-06-12T04:10:09Z","title":"Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03461","snapshot_observed_at":"2026-08-06T19:34:00.144149Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.144149Z"},"links":{"cited_paper":"/paper/1706.03461","citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:725a2cbc84d2d869f711e9e5fcddac97ce8155c0da6d107b15359e370e36f535","observation_id":"c0b1450b-8391-4784-af92-852263e72a6f","resolution":{"observed_at":"2026-08-06T19:34:00.144149Z","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":"2026-08-06T19:34:00.190352Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.190352Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:216489aa70f17030bdea73b8c250af400e2bae45a490211bbb3dfc52dcaefdd0","observation_id":"a0a98738-e73f-4874-9139-ec7cc3428787","resolution":{"observed_at":"2026-08-06T19:34:00.190352Z","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":"2026-08-06T19:34:00.267811Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.267811Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:efba480ba73e126d3545586df50caf77e9439698263a388d083e61c60a75854e","observation_id":"a8647d38-8d8e-4095-8291-4102a93ae730","resolution":{"observed_at":"2026-08-06T19:34:00.267811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.00116","last_updated":"2018-12-01T01:16:24Z","snapshot_observed_at":"2026-08-01T16:34:54.793525Z","submitted_at":"2018-12-01T01:16:24Z","title":"Explore-Exploit: A Framework for Interactive and Online Learning","version":1},"cited_work":{"arxiv_id":"1812.00116","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.00116","snapshot_observed_at":"2026-08-06T19:34:01.924321Z","title":"Explore-Exploit: A Framework for Interactive and Online Learning","venue":"cs.LG","work_id":"80fbbf8b-0a35-4b3a-b2d3-32e18705768b","year":2018},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.351793Z"},"links":{"cited_paper":"/paper/1812.00116","citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:4b998e4e5b3af49ffaebc4c4eac7b2fda95a91482b2f25f17f45e41ac5ea34e9","observation_id":"efb541a6-bf19-4040-b786-17d28c2ecaa6","resolution":{"observed_at":"2026-08-06T19:34:02.012392Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:00.409274Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.409274Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:ef16af5a3668d305ebface02345b230312120862a35d14ffda4a4398e202f475","observation_id":"c9c9805f-b71b-415c-aec4-953331620262","resolution":{"observed_at":"2026-08-06T19:34:00.409274Z","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":"2026-08-06T19:34:00.494444Z","title":"Lunceford and M","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.494444Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:f9384086dfe5fcf0016c5f53d5f6fa9ac304f3737a65801a2c378356aaf708f3","observation_id":"88b094e4-e4c5-43c3-a86c-4b0aae230c65","resolution":{"observed_at":"2026-08-06T19:34:00.494444Z","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":"2026-08-06T19:34:00.540713Z","title":"Manzoor and Leman Akoglu","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.540713Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:a821e2fba30701bf7810bda84aca816865dc9a55dbbd6e7ff4fbb842d74a517d","observation_id":"5319baec-f47a-4580-8b5d-a6c46bbfcace","resolution":{"observed_at":"2026-08-06T19:34:00.540713Z","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":"2026-08-06T19:34:02.778129Z","title":null,"venue":null,"work_id":"208d6724-0127-442e-b779-58255c3bb407","year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.590968Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:5bee0ad5a2545a215e8066ab41ef95dd3b6fddfc806d6c5e16c082204a96b2e4","observation_id":"86de5618-1729-439b-9f8e-13c39fe95ab7","resolution":{"observed_at":"2026-08-06T19:34:02.841709Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:02.608201Z","title":null,"venue":null,"work_id":"2db44efc-53fb-480f-8f35-408c5150f2aa","year":1923},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.677552Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:5c17de878b45330ddf38e5f487f2175edc53a3f094140c6df57b2736466e9dde","observation_id":"112e11fd-1ff4-4902-8843-2bbe44f8e485","resolution":{"observed_at":"2026-08-06T19:34:02.657219Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:00.808017Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.808017Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:e15589010922f148c163d908729277bceb1bdbb0a79616eefa952e8b0c9806de","observation_id":"136c555f-25b3-4cf5-8547-bb111d51b803","resolution":{"observed_at":"2026-08-06T19:34:00.808017Z","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":"2026-08-06T19:34:00.953703Z","title":"Nocedal and S","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:00.953703Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:23b8cdd0b7cc6f0be1274e6988f90d42725598c2fe9e1e0e04f7419346cc02c9","observation_id":"e0bd797a-1f36-46eb-bc9e-95d00616ecb8","resolution":{"observed_at":"2026-08-06T19:34:00.953703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.00102","last_updated":"2017-07-01T06:41:00Z","snapshot_observed_at":"2026-08-06T05:49:23.578859Z","submitted_at":"2017-07-01T06:41:00Z","title":"Some methods for heterogeneous treatment effect estimation in high-dimensions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.00102","snapshot_observed_at":"2026-08-06T19:34:01.016397Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.016397Z"},"links":{"cited_paper":"/paper/1707.00102","citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:22af48a6a206a036f3e71419bad1e2ba1401f66bfc53393f4d2fb8e1db564bcd","observation_id":"6a0dcd16-706c-4bcb-9b12-7bdc471f54e9","resolution":{"observed_at":"2026-08-06T19:34:01.016397Z","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":"2026-08-06T19:34:02.456387Z","title":"and Rubin D.B","venue":null,"work_id":"d61b76f8-3c8a-48d0-8dbc-497267e44e15","year":1983},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.096365Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:df3c5c59aef68386848882484ffab17c5048187ae29260fdec7dc2dcdd594637","observation_id":"ebb1de7b-3638-4377-a4a4-45dc1d42aa5e","resolution":{"observed_at":"2026-08-06T19:34:02.536892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:01.183084Z","title":null,"venue":null,"work_id":null,"year":1974},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.183084Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:111eeda6eb0e549a5305ea1c9b45d86461d48c9d697dc522724901304c699ddd","observation_id":"32763137-b6d3-47e4-b953-968a1ad8dd60","resolution":{"observed_at":"2026-08-06T19:34:01.183084Z","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":"2026-08-06T19:34:01.300982Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.300982Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:f454e703394be5da688b9abcfa90edaa400fd3de03cd064e13e3a2624934bd0f","observation_id":"f4739d29-937c-4845-ae42-4590fc4c9dc8","resolution":{"observed_at":"2026-08-06T19:34:01.300982Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-07-06T05:27:13.416519Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-06T19:34:01.454202Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.454202Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:4b23de8c62fa7b8d9c5d9e26ddb6f263e39d580d37502f0a15a8cf142024abbb","observation_id":"76c5faaf-37d0-4732-9500-ef580000d043","resolution":{"observed_at":"2026-08-06T19:34:01.454202Z","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":"2026-08-06T19:34:02.318269Z","title":null,"venue":null,"work_id":"53ceb40d-edaf-4a42-9b77-c6ad83a31ab1","year":2019},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.555810Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:0861ca94498cdd6076de9accbb6460939871e12a4edb41fac3f59a41e4af97da","observation_id":"0c7a59b4-e74e-420c-8cb4-27ed87947b8a","resolution":{"observed_at":"2026-08-06T19:34:02.370238Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:01.628953Z","title":"Vafeiadis, K.I","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.628953Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:4ce4f6987c6be4993c307d122fc086d5c6fa65b70a7a3b6a7196c5c7d3a3b75d","observation_id":"37d226e3-f98a-4085-9929-f74a7b40470a","resolution":{"observed_at":"2026-08-06T19:34:01.628953Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-06T19:34:01.688268Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.688268Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:1f6af9eec4fe803071032674a2de9555b7a972d8e72323151ddd4bc4c3b24c90","observation_id":"5d45b3c4-9228-48f4-b173-2ad728006b4d","resolution":{"observed_at":"2026-08-06T19:34:01.688268Z","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":"2026-08-06T19:34:02.226578Z","title":null,"venue":null,"work_id":"81f74855-6c81-4099-bc2a-7c300e6eea12","year":2017},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.746779Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:b3203c367c90d34f4d1759a2c16a38134448e4d67544647d60b810bd2db5f497","observation_id":"351db8a5-7228-419f-b8ae-141810060f67","resolution":{"observed_at":"2026-08-06T19:34:02.267017Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:34:02.087505Z","title":"We pre-filter and only consider two types of forests: ‘Spruce-Fir’ and ‘Lodgepole Pine ’, and use data for all forests above the median elevation","venue":null,"work_id":"efe0b7e2-317b-4946-9b89-2bdc9f231922","year":null},"citing_paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth","version":1},"reference_index":2007,"source":"pdf_text","source_observed_at":"2026-08-06T19:34:01.816574Z"},"links":{"citing_paper":"/paper/2507.05510"},"observation_digest":"sha256:2dc82d9dd534b064e33f5ec9236e138a13f647de032ef4b44a32e8d0499b2852","observation_id":"5053e90a-dd9c-4416-8a28-6f41031ed7ba","resolution":{"observed_at":"2026-08-06T19:34:02.137899Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.05510","last_updated":"2025-07-07T22:08:45Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T19:22:25.020103Z","submitted_at":"2025-07-07T22:08:45Z","title":"Heterogeneous Causal Learning for Optimizing Aggregated Functions in User Growth"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":30,"verified_exact":1,"verified_fuzzy":2},"total_outbound_references":34},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2507.05510."}