{"id":"W4386305978","doi":"10.2196/48763","title":"Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation","year":2023,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agricultural Research Institute of Ontario; University of Ottawa","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Checklist; Guideline; Systematic review; Inclusion (mineral); Inclusion and exclusion criteria; Quality (philosophy); MEDLINE; Computer science; Quality Score; Set (abstract data type); Medicine; Medical physics; Data science; Psychology; Pathology; Alternative medicine; Operations management; Engineering; Metric (unit)","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":[0.5530497,0.004585677,0.01042122,0.0456647,0.006501214,0.01873312,0.01806225,0.01344985,0.01511573],"category_scores_gemma":[0.8316742,0.006116212,0.02342785,0.03278059,0.008725672,0.01320183,0.01462731,0.01520803,0.01144076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01612101,"about_ca_system_score_gemma":0.07422114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00919315,"about_ca_topic_score_gemma":0.005914458,"domain_scores_codex":[0.2340484,0.2773353,0.4168409,0.0103781,0.05760049,0.003796787],"domain_scores_gemma":[0.06793299,0.4265051,0.1507784,0.06660448,0.2843796,0.003799499],"domain_codex":"reporting","domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":"reporting","study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001084952,0.000268645,0.00660022,0.3595575,0.003310988,0.0005728285,0.006678213,0.002062403,0.002051923,0.02073377,0.3825234,0.2145552],"study_design_scores_gemma":[0.001167766,0.0003455387,0.005841798,0.4545711,0.00350544,0.0006659529,0.00287316,0.002380869,0.003525174,0.01861378,0.5059522,0.0005572943],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006583905,0.135799,0.3572294,0.1057704,0.0327645,0.2350566,0.08804758,0.009777092,0.02897158],"genre_scores_gemma":[0.02071016,0.05235081,0.5065007,0.01492813,0.003255886,0.3643152,0.03247143,0.001740843,0.003726874],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4469503,"threshold_uncertainty_score":0.5511693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7286857415267036,"score_gpt":0.6306642509162856,"score_spread":0.09802149061041798,"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."}}