{"id":"W4240259051","doi":"10.1515/iupac.87.0421","title":"Nervous System","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Diet and metabolism studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Relation (database); Chemical nomenclature; Computer science; Psychology; 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":[0.0007278545,0.001283599,0.001223477,0.003136047,0.0006157259,0.0023641,0.001976787,0.001187495,0.09711843],"category_scores_gemma":[0.007242912,0.0004296108,0.001471005,0.005291843,0.0002984466,0.001613292,0.0018008,0.001541499,0.09086336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001386169,"about_ca_system_score_gemma":0.002711304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01714624,"about_ca_topic_score_gemma":0.02948173,"domain_scores_codex":[0.9989518,0.0001464732,0.0002681217,0.0003120121,0.0001956358,0.000125876],"domain_scores_gemma":[0.9973484,0.0006324205,0.0004526925,0.000555303,0.0008162643,0.0001948249],"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":[0.0002014909,0.00001559598,0.003789241,0.00300888,0.00009725175,0.00005839595,0.00003683383,0.000249319,0.0001423236,0.001320554,0.9775054,0.01357478],"study_design_scores_gemma":[0.0001157015,0.00001715949,0.008607301,0.001083585,0.00006239967,0.0001687247,0.00005742599,0.0001364386,0.0001512057,0.001358937,0.9882207,0.00002056251],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001740308,0.0002806537,0.00009684187,0.00007874209,0.0000394708,0.00001953244,0.9969791,0.0001388258,0.002192869],"genre_scores_gemma":[0.0007803799,0.0003477268,0.0003623685,0.0001463154,0.00001736508,0.00009764518,0.9966362,0.00004569486,0.001566249],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09711843,"threshold_uncertainty_score":0.3248935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609415962874484,"score_gpt":0.3945089168241956,"score_spread":0.3784147571954508,"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."}}