{"id":"W7000844221","doi":"","title":"Heterogeneity in Prediction Research: methods and applications","year":2017,"lang":"en","type":"dissertation","venue":"Data Archiving and Networked Services (DANS)","topic":"Statistical Methods in Epidemiology","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Economic and Social Research Council; Canadian Institutes of Health Research; Erasmus Universitair Medisch Centrum Rotterdam; Genentech; Heart and Stroke Foundation of Canada; Department for International Development; Boston Scientific Corporation; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences; National Institutes of Health; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Nucleofection; Gestational period; TSG101; Diafiltration; Dysgeusia; Hyporeflexia; Proteogenomics; Liquation","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.009915927,0.0003289395,0.0007312315,0.0002492978,0.0006026185,0.0001246263,0.001432848,0.0003645611,0.000007798845],"category_scores_gemma":[0.002195514,0.0003030927,0.00003311814,0.0001665619,0.0002758699,0.0001853174,0.0006749603,0.00114972,0.000002683031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003527568,"about_ca_system_score_gemma":0.00004718626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006634986,"about_ca_topic_score_gemma":0.00948652,"domain_scores_codex":[0.9939514,0.003400019,0.0006946772,0.001146232,0.0002572431,0.0005504657],"domain_scores_gemma":[0.9831467,0.0141118,0.0003894372,0.002102936,0.00006899772,0.0001801064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002900504,0.0001813389,0.02038895,0.006254335,0.0002601753,0.00001728609,0.005143776,0.00001984647,0.0007633573,0.02692997,0.001015107,0.9387358],"study_design_scores_gemma":[0.0003930748,0.00008035673,0.1488218,0.001645549,0.0002334038,0.00002678072,0.001515264,0.09598555,0.00006963636,0.739202,0.01153717,0.0004894218],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3118481,0.00792927,0.6342784,0.0002104427,0.001747352,0.004486546,0.006198353,0.0004302324,0.0328714],"genre_scores_gemma":[0.015189,0.005114605,0.9663478,0.00006029935,0.001037807,0.0006364554,0.01073301,0.0001420662,0.0007389226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9382464,"threshold_uncertainty_score":0.9999421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3595701847584492,"score_gpt":0.581282411860043,"score_spread":0.2217122271015939,"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."}}