{"id":"W4251823584","doi":"10.1515/iupac.79.1058","title":"Congener","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; CAS Registry Number; 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":[],"consensus_categories":[],"category_scores_codex":[0.001038924,0.001813749,0.001993013,0.003975495,0.0009578851,0.002721256,0.002321902,0.00162092,0.1996732],"category_scores_gemma":[0.008259251,0.0006043853,0.002034191,0.006630856,0.0003333827,0.001918916,0.001896901,0.001800162,0.1807783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001248819,"about_ca_system_score_gemma":0.002380821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01761241,"about_ca_topic_score_gemma":0.03248362,"domain_scores_codex":[0.9983176,0.0002547664,0.0003243321,0.0006072192,0.0003293318,0.0001668662],"domain_scores_gemma":[0.9966159,0.0009201647,0.000607666,0.0007845183,0.0008718744,0.0001997642],"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":[0.0002822565,0.00002736904,0.002229142,0.002864785,0.000105517,0.00003981132,0.0000277728,0.0002697482,0.0001796614,0.0009215456,0.9820508,0.01100171],"study_design_scores_gemma":[0.0001904441,0.00002197839,0.004444765,0.0007578432,0.00009382246,0.0000975482,0.00005259481,0.0001104322,0.0001770296,0.001230212,0.9927961,0.00002724002],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001165186,0.000192089,0.00007113558,0.00005325431,0.00002688075,0.00001826031,0.9978465,0.0001093352,0.001566072],"genre_scores_gemma":[0.0005591904,0.000273349,0.0003523762,0.0001827912,0.00002059425,0.0001192157,0.9962252,0.00007128912,0.002195957],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1996732,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843982874446019,"score_gpt":0.4244145973452563,"score_spread":0.4059747686007961,"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."}}