{"id":"W4235098985","doi":"10.1515/iupac.79.2005","title":"Sensitizer","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Health and Medical Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Library science; Chemistry; Philosophy; Biology; Linguistics; 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":[0.00140313,0.002313163,0.001808288,0.002976021,0.0009131064,0.002783414,0.003412443,0.002406724,0.1226305],"category_scores_gemma":[0.008378836,0.0007575917,0.002604515,0.004267452,0.000369596,0.002126887,0.002167091,0.002141013,0.179223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483223,"about_ca_system_score_gemma":0.002662415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01399252,"about_ca_topic_score_gemma":0.03424207,"domain_scores_codex":[0.9985164,0.0002648502,0.0002250423,0.0005081269,0.000323522,0.0001619957],"domain_scores_gemma":[0.9971399,0.0008630031,0.0003056426,0.0008537463,0.0006348802,0.0002028384],"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":[0.0002573876,0.00004267416,0.001626064,0.001878991,0.00007658586,0.00002571777,0.00002537654,0.0004087461,0.0002184626,0.000641806,0.9850247,0.00977345],"study_design_scores_gemma":[0.0003553091,0.00003905559,0.004194284,0.0005306055,0.00009706268,0.000101637,0.00005643143,0.0004836353,0.0005222611,0.002043796,0.991531,0.00004488332],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001823521,0.0002655744,0.0001745068,0.0001006336,0.00004230135,0.0000379797,0.996729,0.0006801211,0.001787434],"genre_scores_gemma":[0.0006470769,0.0002422476,0.0007284542,0.0002312462,0.00001661613,0.0001812256,0.9958467,0.0001386888,0.001967896],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1226305,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05353822111869477,"score_gpt":0.5689879019930952,"score_spread":0.5154496808744005,"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."}}