{"id":"W2417387058","doi":"10.1503/cjs.017314","title":"Users’ guide to the surgical literature: how to perform a high-quality literature search","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Surgery","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Ottawa","funders":"","keywords":"Medicine; Quality (philosophy); MEDLINE; Information retrieval; Data science; World Wide Web; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.03367197,0.002988137,0.006609861,0.02772111,0.001600181,0.005488103,0.004122915,0.005147114,0.3054726],"category_scores_gemma":[0.2023739,0.003034629,0.004401922,0.01887288,0.001909981,0.007098203,0.005656966,0.004538091,0.1558282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001843716,"about_ca_system_score_gemma":0.01654251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005687646,"about_ca_topic_score_gemma":0.01509885,"domain_scores_codex":[0.9692029,0.01241346,0.01120728,0.0009378188,0.005705669,0.0005329362],"domain_scores_gemma":[0.7347732,0.1655542,0.01237649,0.008655877,0.07348995,0.005150336],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002274939,0.00008955009,0.0003490013,0.01334641,0.0001003839,0.0002626522,0.0005544584,0.0002230617,0.0006091816,0.00135023,0.8514572,0.1314303],"study_design_scores_gemma":[0.0005694427,0.0001881512,0.001705082,0.01213253,0.0001692901,0.0008703649,0.0008171052,0.000856693,0.0007622543,0.008164509,0.9734746,0.0002899558],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0049499,0.06107005,0.2322175,0.09705354,0.01739191,0.1208752,0.2417048,0.06198211,0.162755],"genre_scores_gemma":[0.005493764,0.02376265,0.7636326,0.02506387,0.003616746,0.07659778,0.03406717,0.007342164,0.06042322],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.966328,"threshold_uncertainty_score":0.990659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7180382478990839,"score_gpt":0.500504239607359,"score_spread":0.2175340082917249,"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."}}