{"id":"W4254572594","doi":"10.1017/cjn.2019.217","title":"P.126 Enhancing patient understanding of spinal conditions through advanced imaging platforms","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Virtual patient; Neurosurgery; Animation; Virtual reality; Patient satisfaction; Process (computing); Medicine; Computer science; Multimedia; Medical physics; Human–computer interaction; Medical education; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006064889,0.0003378603,0.0001220354,0.0002642956,0.0003479034,0.001131436,0.0003823963,0.0004626258,0.03659744],"category_scores_gemma":[0.002821637,0.00008640517,0.0003955925,0.0001195381,0.0005152902,0.0009442915,0.000999904,0.0007498268,0.003375462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002886725,"about_ca_system_score_gemma":0.0006150751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009145814,"about_ca_topic_score_gemma":0.001247238,"domain_scores_codex":[0.9997324,0.0001043266,0.00001159513,0.00002338364,0.0001008485,0.00002747185],"domain_scores_gemma":[0.9990964,0.0005460171,0.00009146694,0.00004275069,0.0001069389,0.0001164405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005356101,0.001475178,0.02305456,0.0009374683,0.00004514022,0.001272619,0.008010882,0.002063582,0.01676904,0.007135705,0.0641237,0.8745765],"study_design_scores_gemma":[0.0006489789,0.0101806,0.1635816,0.002938566,0.0002756442,0.01752999,0.01899618,0.03137409,0.03396287,0.03738924,0.6827565,0.0003657041],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5389969,0.004308362,0.1026436,0.02700717,0.001215001,0.001463918,0.0012312,0.002016565,0.3211172],"genre_scores_gemma":[0.8983361,0.002961333,0.06012513,0.002151242,0.0002938942,0.0004843657,0.0003109513,0.0001427897,0.03519415],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03659744,"threshold_uncertainty_score":0.1224306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02766354242980697,"score_gpt":0.2599883207851261,"score_spread":0.2323247783553191,"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."}}