{"id":"W4231090571","doi":"10.1515/iupac.88.1365","title":"Splanchnic","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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; Philosophy; Data mining","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":[0.001672945,0.001539265,0.001391196,0.005457522,0.0009354036,0.003635083,0.002552327,0.001703629,0.1929512],"category_scores_gemma":[0.01561785,0.0007305159,0.001838291,0.01003941,0.000428512,0.003197614,0.003351898,0.002142348,0.2113381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001782222,"about_ca_system_score_gemma":0.00389478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01817426,"about_ca_topic_score_gemma":0.03320803,"domain_scores_codex":[0.9978573,0.0003998038,0.0005093647,0.0005388914,0.0004577251,0.0002369677],"domain_scores_gemma":[0.9939165,0.001778077,0.0007399647,0.001332247,0.001865011,0.0003682426],"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":[0.00007102218,0.0000108638,0.0007354094,0.001419842,0.00002634639,0.00001401254,0.00002806281,0.0001028348,0.00007502188,0.0008985882,0.991666,0.004951997],"study_design_scores_gemma":[0.0001123338,0.00001360368,0.002359068,0.0008422392,0.00002335681,0.00004192259,0.00007281423,0.0001359909,0.0001265477,0.001360459,0.9948903,0.00002126526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006819241,0.00009433862,0.0001003009,0.00009190839,0.00003432473,0.00002261265,0.9978067,0.0002959511,0.001485715],"genre_scores_gemma":[0.0002434083,0.0001212329,0.0003609246,0.000115409,0.00001260207,0.0001364999,0.9977102,0.0001265445,0.001173117],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1929512,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386476629984166,"score_gpt":0.4664747388608222,"score_spread":0.4426099725609806,"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."}}