{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007568016,0.0007533923,0.0004453506,0.003184539,0.0003841505,0.001243938,0.0005125835,0.0007555535,0.004073672],"category_scores_gemma":[0.006118752,0.0003466956,0.0003772707,0.001770091,0.0005320211,0.0006045385,0.0006204105,0.0002837281,0.001147452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007165393,"about_ca_system_score_gemma":0.0005040091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02020499,"about_ca_topic_score_gemma":0.02785587,"domain_scores_codex":[0.999095,0.0001558104,0.00007492814,0.0002287939,0.0003771666,0.00006830104],"domain_scores_gemma":[0.9973819,0.0007582037,0.0006713941,0.0002420802,0.0008295348,0.0001168687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001101019,0.000043047,0.7262281,0.0007241638,0.0006974112,0.0005727444,0.0005538913,0.003645475,0.08600813,0.0004687789,0.003305017,0.1766523],"study_design_scores_gemma":[0.000009419003,0.0001176376,0.982217,0.00007668473,0.0001084979,0.0009526152,0.0001172814,0.003464911,0.01070223,0.0003258472,0.001860858,0.00004705371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9394727,0.007250313,0.02943847,0.0003097054,0.00008413927,0.0002721738,0.00621439,0.001337867,0.01562028],"genre_scores_gemma":[0.9841628,0.001211771,0.01207198,0.00008555529,0.00005935908,0.0001117994,0.001169958,0.00008384322,0.00104303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02020499,"threshold_uncertainty_score":0.04017478,"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."}}