{"id":"W2605692486","doi":"10.4172/2155-6180.1000217","title":"Using Available Information in the Assessment of Diagnostic Pro tocols","year":2015,"lang":"en","type":"article","venue":"Journal of Biometrics & Biostatistics","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Data science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001996486,0.00007875966,0.0002623969,0.001061799,0.00002244846,0.0000450766,0.0001480824,0.00005495466,0.00001635223],"category_scores_gemma":[0.007437973,0.00005194615,0.00004548696,0.002586649,0.00004699142,0.0002999066,0.00002594438,0.0002068335,0.000004233334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002801765,"about_ca_system_score_gemma":0.0007744234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001014896,"about_ca_topic_score_gemma":0.000003526764,"domain_scores_codex":[0.9980365,0.00006015666,0.0007384131,0.00004554186,0.0009720173,0.000147342],"domain_scores_gemma":[0.9973534,0.000714323,0.0006919517,0.0001237242,0.001010162,0.0001064104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004687975,0.0008401439,0.8398555,0.0006736197,0.0001788437,0.0007247868,0.00283577,0.002111407,0.002008912,0.003063628,0.08727238,0.05996622],"study_design_scores_gemma":[0.01994423,0.02057629,0.7124136,0.00426617,0.001664155,0.004550031,0.0206258,0.07571378,0.004471217,0.004524,0.130265,0.0009857358],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6005497,0.002139881,0.387465,0.001362358,0.001053922,0.002187857,0.0002006614,0.00001092741,0.005029717],"genre_scores_gemma":[0.8938206,0.0001366387,0.105601,0.0003431226,0.0000765841,0.000002866553,0.000008318016,0.000004141214,0.000006669733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.293271,"threshold_uncertainty_score":0.8904486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.284352562379658,"score_gpt":0.4533224578812681,"score_spread":0.1689698955016101,"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."}}