{"id":"W4293695087","doi":"10.1007/s00415-022-11306-5","title":"Reliability and acceptance of dreaMS, a software application for people with multiple sclerosis: a feasibility study","year":2022,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Innosuisse - Schweizerische Agentur für Innovationsförderung; Universität Basel","keywords":"Reliability (semiconductor); Multiple sclerosis; Neuroradiology; Neurology; Software; Psychology; Reliability engineering; Medical physics; Medicine; Computer science; Engineering; Psychiatry","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":[0.008394532,0.000433658,0.0005841622,0.0008749503,0.00056465,0.0008781914,0.0004361452,0.0006899649,0.001602787],"category_scores_gemma":[0.0241305,0.0004100931,0.001005155,0.0003277308,0.0006867942,0.0009933037,0.001228711,0.0007273867,0.0007074114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003485561,"about_ca_system_score_gemma":0.000614742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009156949,"about_ca_topic_score_gemma":0.00121537,"domain_scores_codex":[0.9949286,0.002096555,0.0006014342,0.0006793271,0.001429711,0.0002643767],"domain_scores_gemma":[0.9886723,0.004651122,0.002101403,0.0006986274,0.003021304,0.0008552088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002816681,0.00310572,0.9247142,0.0006377856,0.0003324543,0.0002773427,0.009464066,0.0001802364,0.002834046,0.0001056063,0.001077885,0.05445389],"study_design_scores_gemma":[0.0003489165,0.01576057,0.9732645,0.000174259,0.0002349154,0.0008088216,0.004946645,0.001535162,0.0009015867,0.0001308072,0.001830618,0.00006330905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981608,0.0001033967,0.0005561686,0.00007067038,0.00001386371,0.0004301512,0.0001736939,0.00001240471,0.000478809],"genre_scores_gemma":[0.9966228,0.0001046871,0.00171859,0.00009778981,0.00002596921,0.0008843538,0.0002300548,0.00000844501,0.0003072344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008394532,"threshold_uncertainty_score":0.04439503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05677276577095176,"score_gpt":0.3219074820892666,"score_spread":0.2651347163183149,"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."}}