{"id":"W4205821691","doi":"10.3410/f.727072621.793562548","title":"Faculty Opinions recommendation of Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain.","year":2019,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Pain Management and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Imaging phantom; Phantom limb; Phantom limb pain; Augmented reality; Phantom pain; Medicine; Randomized controlled trial; Physical medicine and rehabilitation; Physical therapy; Computer science; Surgery; Artificial intelligence; Amputation; Radiology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006370593,0.001834599,0.002215473,0.001236208,0.001029947,0.0024039,0.003837542,0.003247571,0.09594183],"category_scores_gemma":[0.03580303,0.0006838936,0.004015163,0.001536756,0.0004808535,0.001316192,0.002105195,0.002441046,0.04868993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001540805,"about_ca_system_score_gemma":0.005669241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008081818,"about_ca_topic_score_gemma":0.0338345,"domain_scores_codex":[0.9972562,0.001273317,0.0003829452,0.0003561322,0.0005155947,0.0002158064],"domain_scores_gemma":[0.9857594,0.004419863,0.001935638,0.002797572,0.003644479,0.001443038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.004845324,0.0003834231,0.001815798,0.003030915,0.0006766801,0.00002798346,0.00002391535,0.0002712505,0.0001697047,0.0003156482,0.9737037,0.01473574],"study_design_scores_gemma":[0.05835291,0.001460047,0.03011508,0.003822629,0.003208562,0.0002196486,0.0001542672,0.002239126,0.001623806,0.003403185,0.8951765,0.0002241669],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001344997,0.0004482092,0.0004154681,0.001520097,0.0002904066,0.001464179,0.990648,0.0005714757,0.003297222],"genre_scores_gemma":[0.006244628,0.000574165,0.003766678,0.001557886,0.0002056112,0.01001007,0.9678684,0.0003257512,0.00944685],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09594183,"threshold_uncertainty_score":0.3209574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05238208392652172,"score_gpt":0.3813305984007928,"score_spread":0.328948514474271,"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."}}