{"id":"W3113225050","doi":"10.2147/dmso.s283949","title":"&lt;p&gt;Reporting and Methods in Developing Prognostic Prediction Models for Metabolic Syndrome: A Systematic Review and Critical Appraisal&lt;/p&gt;","year":2020,"lang":"en","type":"review","venue":"Diabetes Metabolic Syndrome and Obesity","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"","keywords":"Critical appraisal; Data extraction; Systematic review; Checklist; Medicine; Meta-analysis; MEDLINE; Statistic; Computer science; Intensive care medicine; Statistics; Internal medicine; Psychology; Pathology; Alternative medicine; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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","metaepi_narrow","metaepi_broad"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.007624117,0.001331232,0.0159085,0.0007022834,0.0002859189,0.0002116571,0.000283636,0.0007064283,0.000007966702],"category_scores_gemma":[0.01892409,0.001083592,0.001286775,0.001232336,0.000311518,0.0004873951,0.0003950006,0.0007564429,0.000006899361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000808961,"about_ca_system_score_gemma":0.0005063277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003964251,"about_ca_topic_score_gemma":0.00001166431,"domain_scores_codex":[0.9908971,0.001475795,0.003932724,0.001813264,0.0007145518,0.001166523],"domain_scores_gemma":[0.9937571,0.002678738,0.001546423,0.0009577526,0.0003046235,0.0007553198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000002943965,0.0001001309,0.0002865016,0.8219485,0.002610396,0.000155831,0.0001071976,2.650505e-7,0.000002153518,0.0008758241,0.00001767837,0.1738926],"study_design_scores_gemma":[0.001709372,0.0004178257,0.0118941,0.656895,0.118324,0.007251131,0.00003436811,0.0009084322,0.00001082486,0.0007717043,0.199691,0.002092256],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005546205,0.9801294,0.002980179,0.0001229005,0.0003794422,0.0104326,0.0001703248,0.0002054657,0.00003346412],"genre_scores_gemma":[0.001454235,0.9720085,0.02146199,0.0002350975,0.0001561396,0.004252745,0.0002018874,0.0002028593,0.0000265077],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1996734,"threshold_uncertainty_score":0.9999439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04364197120151695,"score_gpt":0.3506686411425619,"score_spread":0.3070266699410449,"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."}}