{"id":"W2105587708","doi":"","title":"Developing optimal search strategies for detecting clinically sound causation studies in MEDLINE.","year":2003,"lang":"en","type":"article","venue":"PubMed","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Causation; MEDLINE; Gold standard (test); Medicine; Computer science; Epistemology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1925878,0.0001780199,0.001747144,0.000324531,0.0001576647,0.0007175829,0.0005618348,0.00007040863,0.00008184555],"category_scores_gemma":[0.1408587,0.00009569296,0.0005075476,0.001045817,0.00006526098,0.0003318433,0.00006035741,0.0001277976,0.00006666752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000944401,"about_ca_system_score_gemma":0.0001418146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004852768,"about_ca_topic_score_gemma":0.0001656578,"domain_scores_codex":[0.985669,0.004527353,0.006619667,0.0007249924,0.002022856,0.0004361706],"domain_scores_gemma":[0.9816261,0.01406389,0.001779671,0.001040033,0.001392795,0.00009751425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008412075,0.0001422368,0.2795719,0.0007403886,0.001399229,0.00001903368,0.0134512,0.01478855,0.00002877701,0.08396065,0.004361547,0.6014524],"study_design_scores_gemma":[0.002649143,0.0001411787,0.3605435,0.0001518924,0.0004915391,0.00004330007,0.1680194,0.01868063,0.0004386123,0.4150757,0.03233057,0.001434406],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8020812,0.0009819901,0.1919904,0.0004529735,0.0003945676,0.00200635,0.000002156013,0.000007258438,0.002083134],"genre_scores_gemma":[0.9583657,0.0000297139,0.03920018,0.0001104273,0.00006756438,0.001254682,0.000001117567,0.000008430233,0.0009621648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.600018,"threshold_uncertainty_score":0.8663782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9229342170872689,"score_gpt":0.6018530045558815,"score_spread":0.3210812125313873,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}