{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000856799,0.001299597,0.001669101,0.002973113,0.0006292468,0.002452865,0.002372073,0.001630064,0.1243138],"category_scores_gemma":[0.007861399,0.0004640403,0.002341758,0.00444581,0.0002488291,0.001382464,0.001893457,0.001194716,0.1025411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284519,"about_ca_system_score_gemma":0.002067901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01032007,"about_ca_topic_score_gemma":0.02222032,"domain_scores_codex":[0.998901,0.0001827033,0.000242058,0.0003435301,0.0001908452,0.0001397366],"domain_scores_gemma":[0.9978657,0.0005752459,0.0004377777,0.0004835901,0.0004597932,0.0001779818],"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":[0.0004939004,0.00003336698,0.00443481,0.006802413,0.0002803624,0.0001077983,0.00003961445,0.0003721442,0.0003012247,0.0009860304,0.9703475,0.0158009],"study_design_scores_gemma":[0.000595591,0.0000448538,0.009466933,0.002287717,0.0003191627,0.0004246436,0.00007502292,0.0002559001,0.0003538282,0.001595609,0.9845463,0.00003439595],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002838277,0.000635249,0.00008823265,0.000101706,0.00003375261,0.00003195766,0.9965743,0.0002060276,0.002044934],"genre_scores_gemma":[0.001236131,0.0006324664,0.0003816853,0.0003047289,0.00002779147,0.0001577693,0.9951827,0.00007663291,0.002000051],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1243138,"threshold_uncertainty_score":0.415871,"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."}}