{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LMEHWGV7O453YCDHKQSLLBE2GV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b5a9a41ce28645888d56821478f1e0e7a524646522da370b6a693b3391c22558","cross_cats_sorted":["stat.ME"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"econ.EM","submitted_at":"2026-06-27T10:16:20Z","title_canon_sha256":"8576c66a912a3826300ec2e080ec2a380b96a6db0210ac6c6ae828dc8bbb6689"},"schema_version":"1.0","source":{"id":"2606.28848","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.28848","created_at":"2026-06-30T01:16:54Z"},{"alias_kind":"arxiv_version","alias_value":"2606.28848v1","created_at":"2026-06-30T01:16:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28848","created_at":"2026-06-30T01:16:54Z"},{"alias_kind":"pith_short_12","alias_value":"LMEHWGV7O453","created_at":"2026-06-30T01:16:54Z"},{"alias_kind":"pith_short_16","alias_value":"LMEHWGV7O453YCDH","created_at":"2026-06-30T01:16:54Z"},{"alias_kind":"pith_short_8","alias_value":"LMEHWGV7","created_at":"2026-06-30T01:16:54Z"}],"graph_snapshots":[{"event_id":"sha256:59a4b023ca65f8b8233da7cccb1eac69b5697186754bb3ddf47484d62354850a","target":"graph","created_at":"2026-06-30T01:16:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.28848/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Consider an analyst interested in predicting the size of an effect. She has identified a set of prior published studies of similar effects. We provide a toolkit for (i) summarizing the prior literature, (ii) making predictions of effects in new contexts, and (iii) correcting for the bias from selectivity in the prior literature. We illustrate these methods with empirical examples from labor, public, behavioral, environmental, and development economics. Some of the tools are relevant even when only three prior studies are available. We show how it is possible to use covariates to transparently ","authors_text":"Avik Garg, Maximilian Kasy, Peter Ganong","cross_cats":["stat.ME"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"econ.EM","submitted_at":"2026-06-27T10:16:20Z","title":"Literature Review and Evidence Aggregation: a Toolkit for Applied Micro"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28848","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1fa55e14d2a65672ea1d6f74bfafa84ed121eb21eb32909fd2cc2d12f9872a35","target":"record","created_at":"2026-06-30T01:16:54Z","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":"b5a9a41ce28645888d56821478f1e0e7a524646522da370b6a693b3391c22558","cross_cats_sorted":["stat.ME"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"econ.EM","submitted_at":"2026-06-27T10:16:20Z","title_canon_sha256":"8576c66a912a3826300ec2e080ec2a380b96a6db0210ac6c6ae828dc8bbb6689"},"schema_version":"1.0","source":{"id":"2606.28848","kind":"arxiv","version":1}},"canonical_sha256":"5b087b1abf773bbc08675424b5849a3566728026122344380942a1ad926420a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b087b1abf773bbc08675424b5849a3566728026122344380942a1ad926420a3","first_computed_at":"2026-06-30T01:16:54.389281Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T01:16:54.389281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RAaRsnFTQUdx/lVEO58Lou3xKSr3CRBBrzKrQJ076v39hQtldpmMQFefGK/Z/zlmBM3CX+EEbtDkpbL5bQK+Bw==","signature_status":"signed_v1","signed_at":"2026-06-30T01:16:54.389837Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.28848","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1fa55e14d2a65672ea1d6f74bfafa84ed121eb21eb32909fd2cc2d12f9872a35","sha256:59a4b023ca65f8b8233da7cccb1eac69b5697186754bb3ddf47484d62354850a"],"state_sha256":"d099f39c08c24f680ba50991fcc6a5485f212f47e69ca0227461bd55f646a00b"}