{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003010705,0.0003437718,0.0006016635,0.000162176,0.0001178139,0.0001289888,0.0005950343,0.0002456604,0.001817542],"category_scores_gemma":[0.0003942506,0.0003069533,0.0001929027,0.00008350686,0.0001259419,0.00005912684,0.00007819215,0.0007517167,0.00001318389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001515037,"about_ca_system_score_gemma":0.0001580386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001045001,"about_ca_topic_score_gemma":0.000140966,"domain_scores_codex":[0.9982246,0.00001935395,0.000311499,0.0002781627,0.0008074616,0.0003589064],"domain_scores_gemma":[0.9985445,0.00001883999,0.00009255578,0.0009754428,0.0001336145,0.0002350207],"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":[0.00001545831,0.00002847962,0.000003342284,0.000246236,0.0001552937,0.0001305727,9.763839e-7,0.00002515755,0.000002328056,4.191081e-7,0.9740412,0.02535057],"study_design_scores_gemma":[0.0002441726,0.00007486968,0.00001889742,0.0004152945,0.0002372779,0.00001125938,0.000004532063,0.0009522109,0.000004108334,0.0000275581,0.9976728,0.0003370157],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006595696,0.001860421,0.000648831,0.0001710873,0.001072711,0.0000574503,0.9958163,0.0001840691,0.0001231231],"genre_scores_gemma":[0.00009181708,0.001325432,0.0000908142,0.00009201974,0.001223175,0.000005056389,0.9967515,0.00003801644,0.0003821944],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02501355,"threshold_uncertainty_score":0.9999382,"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."}}