{"id":"W4231825851","doi":"10.1515/iupac.87.0718","title":"White Matter","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":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Relation (database); Chemical nomenclature; Psychology; Computer science; Chemistry; Linguistics; Philosophy; Data mining; 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":[0.000703676,0.001711639,0.001708364,0.004459308,0.000911814,0.003563876,0.002292799,0.001858702,0.1983362],"category_scores_gemma":[0.0096566,0.0005502693,0.001389391,0.006848453,0.0003740423,0.002455652,0.001935626,0.001736498,0.2057689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00120747,"about_ca_system_score_gemma":0.002765409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01449613,"about_ca_topic_score_gemma":0.02909986,"domain_scores_codex":[0.998913,0.0001069527,0.000214178,0.0004341054,0.0001951052,0.0001366552],"domain_scores_gemma":[0.9968612,0.0006794324,0.0005149581,0.0007436004,0.0009470174,0.0002538652],"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":[0.000136469,0.00001390737,0.001769697,0.001472291,0.00006021437,0.00004707859,0.00001930504,0.0001014873,0.0001004067,0.0006352952,0.9843598,0.01128399],"study_design_scores_gemma":[0.0001565577,0.00001776798,0.007507158,0.00118416,0.00006702971,0.0002568426,0.00005856519,0.0001551454,0.000231121,0.003159504,0.9871749,0.00003111418],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001671138,0.00034919,0.0001045929,0.0001208201,0.00006171264,0.00002210192,0.9953341,0.0003063208,0.003534016],"genre_scores_gemma":[0.0008024598,0.000391161,0.0004459197,0.0002178836,0.00003935161,0.0001081699,0.9948477,0.0001070702,0.00304045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1983362,"threshold_uncertainty_score":0.6635008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021351606104278,"score_gpt":0.3676803448529923,"score_spread":0.3574668287919495,"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."}}