{"id":"W4255614406","doi":"10.1515/iupac.88.1363","title":"Spinal Cord","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Medical Imaging and Analysis","field":"Engineering","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; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000750659,0.001381323,0.001518847,0.003834441,0.0008699583,0.003007211,0.002498185,0.00179886,0.1906549],"category_scores_gemma":[0.01167064,0.0004325632,0.001537165,0.00636111,0.0003841818,0.002137703,0.002062486,0.001504519,0.190865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001485186,"about_ca_system_score_gemma":0.0032876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02090924,"about_ca_topic_score_gemma":0.04062586,"domain_scores_codex":[0.9987845,0.0001574355,0.0003020869,0.0003796761,0.0002337209,0.0001425868],"domain_scores_gemma":[0.9959227,0.0009963424,0.0005555605,0.0008448799,0.001407531,0.0002729753],"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":[0.0001942391,0.00001348713,0.001863014,0.002542024,0.00006869472,0.00005817998,0.00002413369,0.0001392682,0.00009302953,0.000743502,0.9764189,0.01784156],"study_design_scores_gemma":[0.000164386,0.00002973042,0.008274268,0.002300886,0.00007910295,0.0002604264,0.00008815849,0.0001943869,0.0002150126,0.002394897,0.9859622,0.00003653181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002007116,0.0005929879,0.0001333479,0.0001744019,0.00007755047,0.00003772684,0.9941047,0.0003030218,0.004375656],"genre_scores_gemma":[0.0009963854,0.0006477985,0.0004177491,0.0002743574,0.00003925537,0.0001680873,0.9944988,0.00007734902,0.002880152],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1906549,"threshold_uncertainty_score":0.6378043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187030265898445,"score_gpt":0.4266170377446184,"score_spread":0.4079140111547739,"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."}}