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A Controlled Experimental Evaluation"},"references":{"count":19,"internal_anchors":1,"resolved_work":19,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"Box, G.E.P .; Jenkins, G.M.Time Series Analysis: Forecasting and Control; Holden-Day: San Francisco, CA, USA, 1970","work_id":"0661c3fb-2960-4db1-a275-d0d25bcebc92","year":1970},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"Hyndman, R.J.; Athanasopoulos, G.Forecasting: Principles and Practice, 2nd ed.; OTexts: Melbourne, Australia, 2018","work_id":"87b62e56-7c95-4201-af68-f2b8fd7f02db","year":2018},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"An analysis of transformations.J","work_id":"45aa2d19-2b48-4801-ad7b-f0e63dde7245","year":null},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"The estimation and application of long memory time series models.J","work_id":"8c468aca-03f3-4748-a6e4-8e859933273c","year":1983},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"The M3-Competition: Results, conclusions and implications.Int","work_id":"f54739eb-2b27-4f02-b047-13c9a42a78d0","year":2000}],"snapshot_sha256":"59fa5e0387893fbe80f1f2e7096d8f662b5d6e3103f4cbf32130afc37ece2c7d"},"source":{"id":"2605.17689","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T22:02:52.986390Z","id":"ffc82a68-1974-4e6c-838c-7738d996a9e4","model_set":{"reader":"grok-4.3"},"one_line_summary":"Large-scale experiments on synthetic data find stationarity transformations improve forecasts in only 18% of matched cases, with variance stabilization as the main exception and signal attenuation as the mechanism.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Stationarity transformations improve time series forecasts only 18 percent of the time even when matched to the data.","strongest_claim":"For matched pairs, transforms improve forecasts only 18% of the time. The primary exception is variance stabilization: log and Box-Cox on heteroscedastic data improve accuracy in 60-65% of cases. Mediation analysis confirms that while transforms achieve trend stationarity, this does not translate into lower forecast error; the mechanism is signal attenuation.","weakest_assumption":"The synthetic datasets accurately isolate and represent the non-stationarity types (trend, seasonality, heteroscedasticity) that matter for real forecasting performance, and the consensus ratio from ten statistical tests reliably identifies when a transform is matched to the data."}},"verdict_id":"ffc82a68-1974-4e6c-838c-7738d996a9e4"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ef1614646fee27240c0b1ce8cf7b6c2a0b2c7992f1fcb0998a2d9dcb6286f184","target":"record","created_at":"2026-05-20T00:04:52Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"3e71d1e139436723a54431a90f007ba6887e44ee7c2914b7cfc22ce29a48542e","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-05-17T23:02:53Z","title_canon_sha256":"9286baf2d5d3faa577d5c89e639d594c088e42beb0b7b2a314361c31b1292cdf"},"schema_version":"1.0","source":{"id":"2605.17689","kind":"arxiv","version":1}},"canonical_sha256":"5f4cc108ff2de976ffb8334473208fe1ea0dba1c170e17704b3bc49367936f7d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f4cc108ff2de976ffb8334473208fe1ea0dba1c170e17704b3bc49367936f7d","first_computed_at":"2026-05-20T00:04:52.900283Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:04:52.900283Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Yz6zMP4l3RfM8tFJ8lwBvvXEX9laYUhrEwjI4gvJNQF9D7ayzqM/I9LZ3VJrI4/egXtmhHRsSD36RxxFVkNKDQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:04:52.901185Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17689","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a769d18a1418dd52d7abe768fc5f31fa84f378e77ed5ad9a97ef7e0c0096c3c","sha256:ef1614646fee27240c0b1ce8cf7b6c2a0b2c7992f1fcb0998a2d9dcb6286f184","sha256:28c0b4b0a8afdea221668e003af53b178141fde926a34e4bdbe15005a9da25b6"],"state_sha256":"55a0c2340d040d8201dd47c15b13b070aedad6208b61c86443f5bc9a5ca06681"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GxUn3Njz2JRBFbhQHApbmKDlY03blAygYz5qCj8o0dmrfzB47T1xlZd2Km011TuhiAibdGRwDRDYxQQ4OEMrAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T22:23:21.732162Z","bundle_sha256":"db0beec64fa55825b0dada53aacdfcdcc4e35b0a17563c9e6375429af34e316a"}}