{"id":"W2122547253","doi":"10.1136/qshc.2010.042432","title":"Optimal search filters for detecting quality improvement studies in Medline","year":2010,"lang":"en","type":"article","venue":"BMJ Quality & Safety","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Rigour; MEDLINE; Medicine; Quality (philosophy); Information retrieval; Evidence-based medicine; Computer science; Medical physics; Alternative medicine; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4802155,0.0003642109,0.003919933,0.0002678131,0.0003147431,0.0003288348,0.00154509,0.0001369242,0.001463153],"category_scores_gemma":[0.1639992,0.0001953484,0.001719894,0.0009893655,0.0001859859,0.0002623414,0.0004040913,0.0004420711,0.0002864474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001077076,"about_ca_system_score_gemma":0.0001793339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002531437,"about_ca_topic_score_gemma":0.00200348,"domain_scores_codex":[0.9521911,0.01404322,0.02490727,0.001807334,0.00629651,0.0007545816],"domain_scores_gemma":[0.9492168,0.03674829,0.005680401,0.005318906,0.002731924,0.0003036345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001036696,0.0008401337,0.1047279,0.00296907,0.002223973,0.00001720255,0.03162416,0.002927257,0.04916485,0.01704113,0.0306759,0.7567517],"study_design_scores_gemma":[0.0124253,0.001240856,0.3120111,0.0006691083,0.001060089,0.00003850066,0.3313421,0.08336428,0.01726484,0.03838303,0.1970729,0.005127836],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524709,0.0002212717,0.0387683,0.004149143,0.0008293492,0.002774118,0.0001023052,0.00001360834,0.0006709946],"genre_scores_gemma":[0.9619015,0.00002281249,0.03415546,0.0004606023,0.0003039123,0.0002886465,0.0000164016,0.00001649169,0.002834206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7516239,"threshold_uncertainty_score":0.9994497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.878249717954213,"score_gpt":0.6709630402857252,"score_spread":0.2072866776684879,"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."}}