{"id":"W4237363787","doi":"10.1515/iupac.79.2186","title":"Unit Risk","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; 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":[0.001634487,0.001647029,0.001265852,0.003505718,0.0006788194,0.003420366,0.00252522,0.001562849,0.1923739],"category_scores_gemma":[0.01877568,0.0005451781,0.002580872,0.004131028,0.0003019371,0.002497053,0.001679946,0.002111813,0.1334225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557377,"about_ca_system_score_gemma":0.00238169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01236866,"about_ca_topic_score_gemma":0.01688091,"domain_scores_codex":[0.9975751,0.000454708,0.0004000218,0.0007925773,0.0005743621,0.0002032295],"domain_scores_gemma":[0.9946631,0.002043292,0.0005757425,0.001306413,0.001169883,0.0002415156],"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":[0.0001826517,0.0000327079,0.003378079,0.001224752,0.0001412617,0.00002522558,0.0000218759,0.001134775,0.00005994262,0.002555883,0.9671008,0.02414203],"study_design_scores_gemma":[0.0002407972,0.00003661569,0.004203729,0.0006147767,0.0001067164,0.0001070942,0.00006393269,0.001000953,0.0001787161,0.007363779,0.9860496,0.00003329378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003581897,0.000402151,0.0005823603,0.0002768929,0.000112246,0.0000620162,0.9898027,0.00073726,0.007666145],"genre_scores_gemma":[0.003262707,0.0005345475,0.001852124,0.0005150228,0.00008418741,0.000248269,0.9870717,0.000293492,0.006137994],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1923739,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0146143496927635,"score_gpt":0.3901845292990021,"score_spread":0.3755701796062386,"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."}}