{"id":"W4205669566","doi":"10.1177/20552173211070760","title":"Cervical Spinal Cord Atrophy can be Accurately Quantified Using Head Images","year":2022,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal - Experimental Translational and Clinical","topic":"Spinal Cord Injury Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Spinal cord; Medicine; Cord; Atrophy; Magnetic resonance imaging; Central nervous system disease; Nuclear medicine; Radiology; Pathology; Internal medicine; Surgery","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009095248,0.0002719808,0.000540075,0.000177478,0.00112615,0.0001327747,0.0002264237,0.0001083844,0.001619939],"category_scores_gemma":[0.0001083755,0.0002473424,0.0004747604,0.0002918131,0.0003904548,0.0002085646,0.0001531976,0.001424487,0.000008085581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001758174,"about_ca_system_score_gemma":0.0003170408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001412154,"about_ca_topic_score_gemma":0.00001331309,"domain_scores_codex":[0.996237,0.0004354986,0.00105957,0.0005150365,0.001275542,0.0004773515],"domain_scores_gemma":[0.998549,0.0002915129,0.0001914794,0.000191508,0.0001597148,0.000616718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.1114531,0.004702021,0.2633048,0.00006677741,0.0006488648,0.0005247865,0.0002577192,0.0001172557,0.5865485,0.0004774606,0.0008386502,0.0310601],"study_design_scores_gemma":[0.01852925,0.02897021,0.9143318,0.0002158352,0.0002483443,0.003585114,0.002608091,0.008746809,0.01807556,0.0002950706,0.003647376,0.0007465285],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903513,0.001689529,0.000294171,0.006475474,0.00052643,0.000391577,0.0001403728,0.00003488309,0.0000963269],"genre_scores_gemma":[0.9928354,0.0001583311,0.005039486,0.001138369,0.0006386783,0.00002574649,0.00005617295,0.00004416312,0.00006367525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.651027,"threshold_uncertainty_score":0.9999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.514306738036913,"score_gpt":0.5040454166111249,"score_spread":0.01026132142578806,"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."}}