{"id":"W4245984317","doi":"10.1515/iupac.79.1333","title":"Genotype","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Multidisciplinary approach; Computer science; Toxicology; Chemistry; Biology; Philosophy; Linguistics; Sociology; Social science","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":[0.001378985,0.002009633,0.00153112,0.003119527,0.001069551,0.003464489,0.002823779,0.001921185,0.1975992],"category_scores_gemma":[0.01034523,0.0006324041,0.001859551,0.00575335,0.0003679272,0.002484341,0.002189128,0.001746389,0.2675764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001514832,"about_ca_system_score_gemma":0.002672018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02070616,"about_ca_topic_score_gemma":0.0361388,"domain_scores_codex":[0.9979207,0.0003419563,0.0003093288,0.0007974834,0.0003954798,0.0002351111],"domain_scores_gemma":[0.995699,0.001024392,0.0004028262,0.001261948,0.001344744,0.000267022],"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":[0.0001057251,0.00001626285,0.001309065,0.0007035369,0.00003717995,0.00001728728,0.0000230897,0.0001394362,0.00008808392,0.0006511749,0.9909477,0.005961495],"study_design_scores_gemma":[0.0001379132,0.00001633903,0.003106493,0.0004273558,0.00003987813,0.00005942515,0.00007710263,0.0001874567,0.0001788453,0.001641848,0.9941029,0.00002443385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009052156,0.00007196369,0.0001072608,0.00006905733,0.0000293532,0.00001722554,0.998019,0.0002926107,0.001302965],"genre_scores_gemma":[0.0003020239,0.00007397582,0.0003366147,0.0001310472,0.00000993123,0.0000995498,0.9975349,0.00009238419,0.0014196],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1975992,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172027780422283,"score_gpt":0.4169038914998882,"score_spread":0.3997011134576599,"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."}}