{"id":"W2620664699","doi":"10.1017/cjn.2017.84","title":"C.06 Retraction of scientific publications in neurosurgery","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Academic integrity and plagiarism","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Toronto Public Health","funders":"","keywords":"Impact factor; Neurosurgery; MEDLINE; Medicine; Data extraction; Misattribution of memory; Scientific misconduct; Family medicine; Alternative medicine; Surgery; Political science; Psychiatry; Pathology; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch","research_integrity"],"domain":"evaluation","study_design":"systematic_review","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","bibliometrics","scholarly_communication","research_integrity"],"domain":"evaluation","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0638056,0.0009952058,0.001467869,0.02168411,0.003260829,0.01099064,0.00271451,0.003478821,0.04477101],"category_scores_gemma":[0.3117931,0.0007950705,0.002746236,0.02848307,0.004741287,0.00750606,0.004241373,0.002267419,0.01760029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007222168,"about_ca_system_score_gemma":0.02395257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004818047,"about_ca_topic_score_gemma":0.003440369,"domain_scores_codex":[0.8775824,0.04905912,0.03378517,0.00457541,0.03229163,0.002706271],"domain_scores_gemma":[0.5339484,0.2091413,0.1222735,0.02600607,0.09793216,0.01069858],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008400048,0.00009978301,0.03179706,0.1332839,0.0009238895,0.001861629,0.003522184,0.0002307061,0.00110775,0.01744634,0.2532721,0.5556146],"study_design_scores_gemma":[0.0001513169,0.0002362292,0.03377261,0.1011934,0.000603364,0.005399416,0.002682292,0.000252463,0.001111208,0.00645837,0.8480278,0.0001115047],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02819706,0.677294,0.004901037,0.08062837,0.03091112,0.002157819,0.01301528,0.0007466977,0.1621487],"genre_scores_gemma":[0.278336,0.5980514,0.01903153,0.03077677,0.0213251,0.003278345,0.01073804,0.0007252594,0.03773764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9965212,"threshold_uncertainty_score":0.3374403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0743255195744261,"score_gpt":0.3238876105712863,"score_spread":0.2495620909968602,"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."}}