{"id":"W4240994475","doi":"10.1515/iupac.79.1694","title":"Nodule","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cancer and Skin Lesions","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; Biology; Linguistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001557988,0.001610068,0.001440366,0.002903818,0.0008200259,0.003005964,0.00273939,0.001690548,0.1397216],"category_scores_gemma":[0.01163935,0.0004907392,0.002123047,0.004209921,0.0003360672,0.001768037,0.001700552,0.001642872,0.1861148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001571456,"about_ca_system_score_gemma":0.002926156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01483147,"about_ca_topic_score_gemma":0.03012056,"domain_scores_codex":[0.9978337,0.0003760896,0.000346875,0.0008024767,0.0004081768,0.0002328335],"domain_scores_gemma":[0.9962703,0.0009088521,0.0003753977,0.000958711,0.001183617,0.0003031059],"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":[0.0001654059,0.00002618887,0.001981537,0.0009554902,0.00006247575,0.00002394825,0.00001804894,0.000179226,0.00009351766,0.0006158866,0.9872934,0.008584961],"study_design_scores_gemma":[0.0002631507,0.00002922324,0.004333336,0.0006004343,0.00007093454,0.0001098293,0.00006408182,0.0003285055,0.0002567439,0.001386866,0.9925302,0.00002661634],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001682575,0.0001533793,0.0001331397,0.0001102762,0.00005261744,0.00003694298,0.9971781,0.0002944636,0.001872849],"genre_scores_gemma":[0.0004826912,0.000103565,0.0003702772,0.0001727721,0.0000163306,0.0001446409,0.9972028,0.00006362084,0.001443299],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8602784,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714342971177392,"score_gpt":0.4376321751974725,"score_spread":0.4204887454856986,"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."}}