{"id":"W4243859726","doi":"10.1515/iupac.88.1103","title":"Neural","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001372683,0.00172625,0.001279795,0.004144437,0.001095742,0.003920247,0.003122547,0.002104532,0.2299347],"category_scores_gemma":[0.01462492,0.0006560101,0.001629694,0.007252292,0.0004635162,0.003443223,0.002946645,0.001891525,0.3156157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001909274,"about_ca_system_score_gemma":0.003388113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02014821,"about_ca_topic_score_gemma":0.03866523,"domain_scores_codex":[0.9977176,0.000409186,0.0004136305,0.0006925006,0.0005047728,0.0002622761],"domain_scores_gemma":[0.9948168,0.001296194,0.0004083921,0.0013363,0.00185445,0.0002877993],"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":[0.00006461927,0.00001094295,0.0006669363,0.0008856109,0.00001950002,0.00001171619,0.00002139705,0.0001132097,0.00005831805,0.0008202083,0.9903997,0.006927918],"study_design_scores_gemma":[0.00008744548,0.0000135437,0.001930487,0.0006289529,0.00001914422,0.0000432191,0.00007337339,0.00019034,0.0001445906,0.001769535,0.9950786,0.00002080795],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009751428,0.0001403454,0.0001532214,0.0001536601,0.00005580459,0.00002774597,0.9959495,0.0004447802,0.00297742],"genre_scores_gemma":[0.0003149628,0.0001385084,0.000374834,0.0001525155,0.00001240747,0.0001170064,0.9967932,0.0001009765,0.00199558],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7700652,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02722086901371424,"score_gpt":0.468773849431389,"score_spread":0.4415529804176748,"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."}}