{"id":"W4251180593","doi":"10.1515/iupac.79.1237","title":"Epithelioma","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Nonmelanoma Skin Cancer Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Linguistics; Biology; Organic chemistry","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":[0.0003538847,0.000555194,0.001182468,0.0003410023,0.0001068002,0.00002348283,0.000288113,0.0003965059,0.005706189],"category_scores_gemma":[0.0006089418,0.0003758839,0.0002875966,0.0002418499,0.0002787315,0.00004794783,0.0002601132,0.0005253076,0.00001881331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008584547,"about_ca_system_score_gemma":0.001158987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008920915,"about_ca_topic_score_gemma":0.0003630702,"domain_scores_codex":[0.9968255,0.00005002202,0.0005254283,0.0006489265,0.001397909,0.0005522508],"domain_scores_gemma":[0.9975352,0.0001231691,0.0002585247,0.001270863,0.0005582098,0.0002540654],"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":[0.0004776098,0.0002113489,0.0001676726,0.0003783265,0.0004808528,0.0006605753,0.000009197672,2.543281e-8,0.00001452271,0.000003564713,0.9905315,0.007064793],"study_design_scores_gemma":[0.002302417,0.000614015,0.0007446469,0.001340657,0.0004675348,0.000216615,0.00001536414,2.03992e-7,0.00009424176,0.00008251549,0.9937055,0.0004163544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001395097,0.004243023,0.00003829096,0.003262484,0.001218538,0.0004897409,0.9901811,0.00008298898,0.0003443657],"genre_scores_gemma":[0.00002512176,0.003814934,0.0001061602,0.0008377122,0.003220032,0.00003918357,0.9902148,0.00007368988,0.001668345],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006648439,"threshold_uncertainty_score":0.9998693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01718175699588223,"score_gpt":0.4256387915429953,"score_spread":0.4084570345471131,"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."}}