{"id":"W4245816092","doi":"10.1515/iupac.88.0585","title":"Cervical Rib","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Voice and Speech 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; Data mining; Philosophy","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":[0.0003716348,0.0004527899,0.0009924875,0.0001979399,0.0001983944,0.00008375997,0.0004710842,0.0006561821,0.00586186],"category_scores_gemma":[0.000998141,0.0003735347,0.0003353002,0.00009013354,0.0002094801,0.00007434283,0.0001798383,0.00106349,0.00003083474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002398689,"about_ca_system_score_gemma":0.001397941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003290357,"about_ca_topic_score_gemma":0.001758202,"domain_scores_codex":[0.9971621,0.00003673598,0.0004132543,0.0005442004,0.00135199,0.0004917228],"domain_scores_gemma":[0.9971303,0.00004102135,0.0002477212,0.00177302,0.0004595838,0.0003483725],"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":[0.0003412488,0.0004588792,0.0001241996,0.0004571085,0.0001989353,0.0005662914,0.000009017892,1.714572e-7,0.000002939882,0.000002308437,0.9949026,0.002936272],"study_design_scores_gemma":[0.002263985,0.0004705251,0.0009295793,0.0005436643,0.0005815233,0.00009546321,0.00003750396,0.000005144999,0.000006488424,0.00006546619,0.9946344,0.0003661985],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003364561,0.001194457,0.00001492654,0.004062457,0.0006761783,0.0004065315,0.9927696,0.00007845592,0.0004609511],"genre_scores_gemma":[0.0000470407,0.001591809,0.00007616627,0.001666732,0.001315589,0.00001138233,0.9932398,0.00005027395,0.002001219],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005831026,"threshold_uncertainty_score":0.9998717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224429163340897,"score_gpt":0.4581969136947996,"score_spread":0.4359526220613907,"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."}}