{"id":"W4253911203","doi":"10.1515/iupac.79.1437","title":"Hypervitaminosis","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Terminology; 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":[0.0007852071,0.001256078,0.001695859,0.002608123,0.000578192,0.001825925,0.00175731,0.00152,0.08051416],"category_scores_gemma":[0.007876159,0.0004671029,0.001551405,0.004883487,0.0002333754,0.001104735,0.001390127,0.001445101,0.04212911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001140166,"about_ca_system_score_gemma":0.002016611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01388827,"about_ca_topic_score_gemma":0.0290606,"domain_scores_codex":[0.9988985,0.0001430989,0.0002765379,0.0003911434,0.0001860455,0.0001046982],"domain_scores_gemma":[0.9973054,0.0007819522,0.0006187459,0.0005014804,0.0005923131,0.0002001708],"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":[0.0006451458,0.0000367327,0.006900762,0.004919644,0.0002323007,0.0001062697,0.00003401635,0.0002443214,0.0002582402,0.0006408051,0.9730698,0.01291199],"study_design_scores_gemma":[0.001085617,0.00005738664,0.0317607,0.003138903,0.0003757209,0.0006107212,0.0000992894,0.0002787122,0.0004542037,0.002129135,0.9599372,0.00007240445],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002518735,0.0003400315,0.00005462614,0.00006561141,0.00002454714,0.00002518127,0.9982464,0.00006565572,0.0009260394],"genre_scores_gemma":[0.001197663,0.0004140447,0.0003068883,0.0001958885,0.00002003649,0.0001936534,0.9966295,0.00003164236,0.001010636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08051416,"threshold_uncertainty_score":0.2693467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006481212079697936,"score_gpt":0.3156291444088014,"score_spread":0.3091479323291034,"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."}}