{"id":"W2803515868","doi":"10.1089/neu.2017.5478","title":"High-Speed Fluoroscopy to Measure Dynamic Spinal Cord Deformation in an <i>In Vivo</i> Rat Model","year":2018,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Spinal Cord Injury Research","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Menzies Centre for Australian Studies, King's College London, University of London; Natural Sciences and Engineering Research Council of Canada; International Collaboration on Repair Discoveries; Centre for Hip Health and Mobility","keywords":"Spinal cord; Anatomy; Cord; Displacement (psychology); Fluoroscopy; Deformation (meteorology); Spinal cord injury; Medicine; White matter; Bead; Dorsum; Materials science; Biomedical engineering; Surgery; Composite material; Magnetic resonance imaging; Radiology","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":[0.0004851706,0.0009159632,0.0003992635,0.0006790186,0.0002553188,0.0003801075,0.0006508332,0.0007664648,0.001375926],"category_scores_gemma":[0.0003047356,0.0003489392,0.0005404374,0.0003845871,0.000544364,0.0005802935,0.0003581325,0.001110275,0.0003370318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006151464,"about_ca_system_score_gemma":0.0006660593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004540216,"about_ca_topic_score_gemma":0.007214916,"domain_scores_codex":[0.999759,0.00002426136,0.00001742198,0.00006683989,0.00008256995,0.00004989918],"domain_scores_gemma":[0.9996532,0.0000580751,0.0001349213,0.00004520363,0.00006746377,0.00004117321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000681864,0.00005612937,0.0004310204,0.00005914405,0.000008272816,0.00003575638,0.00002286412,0.0005421561,0.995302,0.000097895,0.00005162346,0.003324909],"study_design_scores_gemma":[0.00001754664,0.001312425,0.007317982,0.00002107365,0.00006118319,0.0002549453,0.00005519277,0.00686251,0.9829141,0.00007656919,0.001083761,0.00002264271],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8507342,0.002299043,0.1425804,0.0002358829,0.00009562761,0.0002450643,0.0005210618,0.0009801032,0.002308531],"genre_scores_gemma":[0.8960349,0.003886391,0.09295467,0.000123869,0.00002672963,0.0003643203,0.0004999812,0.0001139161,0.005995212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004540216,"threshold_uncertainty_score":0.009027541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1086789171202801,"score_gpt":0.4133586840722978,"score_spread":0.3046797669520177,"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."}}