{"id":"W4245289687","doi":"10.22541/au.158022310.05444580","title":"Validating prediction models for use in clinical practice: concept, steps and procedures","year":2020,"lang":"en","type":"dataset","venue":"Authorea","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Predictive modelling; Computer science; Set (abstract data type); Clinical Practice; Model validation; Machine learning; Quality (philosophy); Data mining; Artificial intelligence; Data science; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04298915,0.00154776,0.001307243,0.004472815,0.001300094,0.005814888,0.003854671,0.00195636,0.007644835],"category_scores_gemma":[0.1603862,0.0009711966,0.001826198,0.005138112,0.001423861,0.004310593,0.004327013,0.00556119,0.006358543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00244161,"about_ca_system_score_gemma":0.00679109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006283735,"about_ca_topic_score_gemma":0.007821345,"domain_scores_codex":[0.9785917,0.01221211,0.002864539,0.002160097,0.00383646,0.0003349436],"domain_scores_gemma":[0.9122083,0.05918482,0.003348592,0.01471691,0.009823715,0.0007177495],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007715216,0.0007227407,0.04492102,0.003652631,0.0009486477,0.000378704,0.0007759394,0.06157261,0.001233739,0.05878177,0.3571034,0.4691373],"study_design_scores_gemma":[0.0009565255,0.0005311299,0.01960815,0.004050134,0.00038822,0.0009468984,0.0007814941,0.4318368,0.008151051,0.2105017,0.3218646,0.0003833566],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0204613,0.002401515,0.8114999,0.009926862,0.00107278,0.008093349,0.1178406,0.01491252,0.01379118],"genre_scores_gemma":[0.0555826,0.001048548,0.8365406,0.001134624,0.0001848307,0.01313299,0.09004628,0.0008641307,0.001465376],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9570109,"threshold_uncertainty_score":0.2273511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1121147470637734,"score_gpt":0.4174435521103545,"score_spread":0.3053288050465811,"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."}}