{"id":"W4239840148","doi":"10.1515/iupac.88.1372","title":"Sterilization","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Computer science; Linguistics; Philosophy","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000440356,0.0004370274,0.0009318768,0.0002771931,0.0001181565,0.000142067,0.0003871796,0.000316543,0.001626056],"category_scores_gemma":[0.002727716,0.0003648157,0.0001607727,0.0001084081,0.0003337067,0.0001697275,0.0001837626,0.0006456377,0.00001231429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003742132,"about_ca_system_score_gemma":0.001070452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006897535,"about_ca_topic_score_gemma":0.0001003136,"domain_scores_codex":[0.9970673,0.00002844976,0.0004814106,0.0005190837,0.001524809,0.0003789619],"domain_scores_gemma":[0.9966943,0.00003949468,0.0003877187,0.001805088,0.0007844588,0.0002888898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002714615,0.0002937541,0.00007213598,0.0006503359,0.0001255022,0.0005147755,0.000007511348,4.0702e-7,0.000009584778,0.000001206482,0.9916732,0.006380104],"study_design_scores_gemma":[0.001857017,0.0004917621,0.0004279265,0.002024845,0.0005126876,0.0002144382,0.00001527963,0.0000203929,0.00001253267,0.00003661267,0.9940857,0.0003008248],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001118986,0.0007293987,0.0001177136,0.001535624,0.001389786,0.000491248,0.9945101,0.0001172429,0.0009970386],"genre_scores_gemma":[0.00004251633,0.0005027853,0.0001367423,0.001282561,0.001728214,0.00001057875,0.9926587,0.00006428108,0.003573627],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006079279,"threshold_uncertainty_score":0.9998804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02545248924881902,"score_gpt":0.4796523217940931,"score_spread":0.4541998325452741,"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."}}