{"id":"W2168292916","doi":"10.1016/j.amjsurg.2012.11.017","title":"Capture-mark-recapture to estimate the number of missed articles for systematic reviews in surgery","year":2013,"lang":"en","type":"article","venue":"The American Journal of Surgery","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Simon Fraser University; St. Joseph’s Healthcare Hamilton; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Systematic review; Citation; Mark and recapture; Closeness; Confidence interval; Systematic error; MEDLINE; Medicine; Computer science; Statistics; Biology; Mathematics; Library science; Environmental health; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2517487,0.005676619,0.01883281,0.01679501,0.00327388,0.006336429,0.01014027,0.008551997,0.008344427],"category_scores_gemma":[0.5976332,0.004814367,0.03716009,0.0131331,0.002815558,0.007728485,0.006392227,0.004877394,0.001868842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002350369,"about_ca_system_score_gemma":0.004658029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008070389,"about_ca_topic_score_gemma":0.01293933,"domain_scores_codex":[0.6603056,0.2492922,0.03785601,0.03820854,0.01217492,0.002162643],"domain_scores_gemma":[0.2829604,0.6218927,0.03662032,0.0503685,0.006816609,0.001341506],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0111325,0.0004170694,0.1446451,0.06545687,0.5614717,0.002321363,0.001803658,0.02553859,0.001679639,0.009031832,0.01880773,0.157694],"study_design_scores_gemma":[0.007059745,0.003658598,0.07890453,0.01163994,0.6060458,0.00635461,0.001003589,0.1803178,0.006429188,0.05861384,0.03854857,0.001423764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09476855,0.1436096,0.7096748,0.004491765,0.003196858,0.01104793,0.0249996,0.005389811,0.002821093],"genre_scores_gemma":[0.5981774,0.005199823,0.3714962,0.002604598,0.0005633073,0.01192444,0.007403126,0.0005753863,0.00205565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7482513,"threshold_uncertainty_score":0.9227271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5075299530006472,"score_gpt":0.4873899547774839,"score_spread":0.02013999822316326,"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."}}