{"id":"W4240833357","doi":"10.1515/iupac.88.0552","title":"Bronchopulmonary Segment","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Data mining; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002907597,0.0005697732,0.0007099374,0.00009438013,0.0001995174,0.00008047993,0.0009606393,0.0005187482,0.004065051],"category_scores_gemma":[0.0003306818,0.0004986026,0.0003155365,0.00007731327,0.0001196828,0.00008869053,0.0007235471,0.001037811,0.00002999194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007008476,"about_ca_system_score_gemma":0.0001449565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003726656,"about_ca_topic_score_gemma":0.0001707176,"domain_scores_codex":[0.9970798,0.00002052445,0.0005229824,0.0006531314,0.001148258,0.000575274],"domain_scores_gemma":[0.9976455,0.0000616828,0.0002871625,0.001601934,0.0001360961,0.0002676253],"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":[0.0001087985,0.0002654449,0.00000197801,0.0004640727,0.0001616175,0.0001688882,0.000005190877,0.0001609241,0.000125444,0.000006635292,0.994341,0.004190065],"study_design_scores_gemma":[0.0006898252,0.00005017478,0.00001223594,0.0004497605,0.0002018782,0.000008436733,0.00000655364,0.0004038315,0.0001261543,0.00005903352,0.9973743,0.0006178045],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004603441,0.001219438,0.0002824415,0.0005373324,0.0007988018,0.0002799229,0.9964179,0.0001534149,0.0002647066],"genre_scores_gemma":[0.00002939237,0.001874914,0.0001056743,0.0002029896,0.001439869,0.00002384008,0.9939655,0.00005645954,0.002301336],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004035059,"threshold_uncertainty_score":0.9997466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01277257422289073,"score_gpt":0.3721344486461063,"score_spread":0.3593618744232156,"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."}}