{"id":"W4242743071","doi":"10.1002/(issn)1708-945x","title":"Canadian Journal of Statistics","year":2018,"lang":"en","type":"paratext","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Statistics; Library science; Geography; Data science; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001755282,0.0006704067,0.001888704,0.001576588,0.0003937065,0.0004657412,0.001359205,0.0006714677,0.02310797],"category_scores_gemma":[0.01251049,0.0006114055,0.0002401777,0.000417581,0.0009061104,0.0001540967,0.00002430753,0.001962632,0.0005739367],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001332405,"about_ca_system_score_gemma":0.04414007,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0503738,"about_ca_topic_score_gemma":0.4698479,"domain_scores_codex":[0.9943149,0.0004940335,0.002877526,0.0002827863,0.0008180526,0.001212677],"domain_scores_gemma":[0.9830733,0.002993453,0.003543163,0.000508351,0.005426808,0.004454909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000185629,0.00001726108,0.0001079443,0.0003795629,0.0002904437,0.002273279,0.000527539,0.000002669379,0.000002289605,0.1481914,0.8359985,0.01219059],"study_design_scores_gemma":[0.0006136482,0.0009852363,0.0002064213,0.001290114,0.0007216783,0.00145404,0.0002134877,0.000070375,0.00002764581,0.5503973,0.4433325,0.0006875698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000453043,0.001177357,0.9358813,0.0001875042,0.01045998,0.0001999186,0.03956139,0.000002345794,0.01248493],"genre_scores_gemma":[0.0009139068,0.0003148167,0.9837066,0.0002499575,0.002781064,0.000001753519,0.0001185706,0.0001692848,0.01174405],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4194742,"threshold_uncertainty_score":0.9996337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05925370840004699,"score_gpt":0.3410722214921932,"score_spread":0.2818185130921462,"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."}}