{"id":"W4235393281","doi":"10.1515/iupac.82.0023","title":"Risk Assessment, Risk Management, and Safety","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":"Terminology; Glossary; Meaning (existential); Computer science; Chemical nomenclature; Management science; Risk analysis (engineering); Engineering ethics; Data science; Epistemology; Medicine; Chemistry; Linguistics; Engineering; Philosophy","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":[0.002141923,0.001586214,0.001281258,0.004597192,0.0007323815,0.002822383,0.00262399,0.001869817,0.04755434],"category_scores_gemma":[0.01925856,0.0006040147,0.002003624,0.00727133,0.000483972,0.002616603,0.002454464,0.002438561,0.03983008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002521933,"about_ca_system_score_gemma":0.003695027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01903845,"about_ca_topic_score_gemma":0.02751267,"domain_scores_codex":[0.9975515,0.0005806689,0.0005104402,0.0005933479,0.0005766833,0.0001875034],"domain_scores_gemma":[0.9935581,0.002776342,0.0009554739,0.001098874,0.001245184,0.0003660239],"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":[0.0001196111,0.00003278852,0.004213477,0.003092413,0.00007819702,0.00003601726,0.00003387554,0.001031433,0.00006781019,0.002603698,0.9732836,0.01540714],"study_design_scores_gemma":[0.0001583258,0.00002152575,0.007033989,0.001361607,0.00005828198,0.0001380554,0.00008521681,0.001001933,0.000175023,0.007541847,0.9823881,0.00003605782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002910526,0.0007434902,0.0004441499,0.0004464129,0.00005521452,0.00004587802,0.9951012,0.0002537113,0.002618995],"genre_scores_gemma":[0.001465815,0.0008478776,0.001612264,0.000302976,0.00002995683,0.0001901973,0.9943714,0.00005287632,0.001126791],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04755434,"threshold_uncertainty_score":0.1590852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008338953773273835,"score_gpt":0.3730860806439595,"score_spread":0.3647471268706857,"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."}}