{"id":"W1857415707","doi":"10.1111/j.1475-6773.2010.01159.x","title":"Derivation and Validation of a MEDLINE Search Strategy for Research Studies That Use Administrative Data","year":2010,"lang":"en","type":"article","venue":"Health Services Research","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Ottawa Hospital","funders":"","keywords":"MEDLINE; Confidence interval; Medicine; Health care; Information retrieval; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.198519,0.00009411464,0.0002823023,0.0004471584,0.001856709,0.0001347722,0.0007345824,0.0002064541,0.0000499324],"category_scores_gemma":[0.01560879,0.00008502947,0.0000185026,0.001029331,0.001484489,0.000755147,0.0004174195,0.0008576461,0.000005062744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007654102,"about_ca_system_score_gemma":0.002420404,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01578273,"about_ca_topic_score_gemma":0.08144177,"domain_scores_codex":[0.9646671,0.03176026,0.0004146261,0.000621301,0.00156216,0.0009745673],"domain_scores_gemma":[0.9310262,0.06510591,0.0001489753,0.0006559647,0.002776585,0.0002863898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.02843769,0.001093225,0.1729981,0.007220788,0.0004398717,0.00001901835,0.6075178,0.00001561426,0.01771495,0.05288155,0.00437005,0.1072914],"study_design_scores_gemma":[0.001913811,0.002341279,0.3652343,0.0004162578,0.00001486098,0.00000530916,0.5674366,0.001613087,0.02340293,0.01288059,0.02438428,0.0003566829],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905398,0.0006843446,0.0001078507,0.006643354,0.0001479573,0.001520075,0.0001689269,0.00002069457,0.0001669864],"genre_scores_gemma":[0.9902349,0.002631666,0.006187543,0.00008196081,0.0001897754,0.0001006019,0.0001763907,0.00001357116,0.0003835991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1922362,"threshold_uncertainty_score":0.9994428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9449188772914475,"score_gpt":0.7393531340647561,"score_spread":0.2055657432266914,"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."}}