{"id":"W4398781267","doi":"10.1017/cjn.2024.101","title":"E.4 Machine learning based patient classification to predict neurological deterioration in mild Degenerative Cervical Myelopathy","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Cervical and Thoracic Myelopathy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services","funders":"","keywords":"Medicine; Myelopathy; Spinal cord compression; Cord; Cervical spondylosis; Spinal cord; Compression (physics); Asymptomatic; Spinal stenosis; Surgery; Pathology; Lumbar","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001774552,0.000514623,0.0005084216,0.002374462,0.0002794557,0.0007716961,0.0004547752,0.0009524871,0.00384332],"category_scores_gemma":[0.007181321,0.00009582075,0.0005053771,0.0008393899,0.0002366043,0.0004439318,0.0004872225,0.0004891588,0.0007622111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004525722,"about_ca_system_score_gemma":0.0005346493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002134304,"about_ca_topic_score_gemma":0.002058937,"domain_scores_codex":[0.9992393,0.0002622373,0.0001391086,0.00009531369,0.0001710019,0.00009299678],"domain_scores_gemma":[0.9964719,0.002220913,0.000451224,0.00012998,0.0005076336,0.0002183725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006720698,0.0002385972,0.942881,0.00005098806,0.000136257,0.0001594907,0.00003724821,0.01012444,0.0005933191,0.0001836895,0.001390495,0.04353247],"study_design_scores_gemma":[0.0001022036,0.0009849524,0.6267514,0.00009101731,0.0001498637,0.001381676,0.0002291437,0.364807,0.001606251,0.002292987,0.001549279,0.00005413115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806889,0.0004922753,0.01158783,0.000563373,0.00007318589,0.0001542716,0.00300275,0.0002598828,0.003177553],"genre_scores_gemma":[0.9926984,0.00006552192,0.005235325,0.00004094455,0.00002469537,0.00006096143,0.001403521,0.000004981915,0.0004656094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00384332,"threshold_uncertainty_score":0.01285714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04284811638788166,"score_gpt":0.2850133251629343,"score_spread":0.2421652087750526,"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."}}