{"id":"W4244491826","doi":"10.1515/iupac.88.1298","title":"Rhombencephalon","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Neurological and metabolic disorders","field":"Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002939299,0.0004195618,0.0009945319,0.0001371125,0.0001560508,0.00005328911,0.0004214364,0.0004450285,0.004600147],"category_scores_gemma":[0.001236897,0.0002996846,0.0002924682,0.0000827767,0.0003020532,0.00005383359,0.0001782232,0.0008736904,0.00001468253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006206727,"about_ca_system_score_gemma":0.0007045544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001333079,"about_ca_topic_score_gemma":0.0002014685,"domain_scores_codex":[0.9975535,0.00004302964,0.000358464,0.0005664677,0.001031157,0.0004473671],"domain_scores_gemma":[0.9977676,0.00003749854,0.0002705309,0.001300605,0.0003013297,0.0003224918],"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":[0.0003725423,0.0004910932,0.00003796275,0.0001822491,0.00008754869,0.0004829215,0.00000319804,2.046814e-7,0.000008849071,0.00000602833,0.9882159,0.01011155],"study_design_scores_gemma":[0.001611302,0.0006778126,0.0009255672,0.0001887144,0.0004217136,0.00008734051,0.000007571192,0.000001555269,0.00000626807,0.0001523915,0.9956363,0.0002833987],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006568775,0.001525086,0.000008320846,0.001943303,0.0009491347,0.0004126359,0.9937461,0.00007700649,0.0006815463],"genre_scores_gemma":[0.00008966563,0.002986592,0.00003679173,0.002274657,0.0009778221,0.00001501522,0.9915613,0.00002916182,0.002028997],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009828153,"threshold_uncertainty_score":0.9999455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235301633394817,"score_gpt":0.4506624981008119,"score_spread":0.4271323347613302,"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."}}