{"id":"W4387519905","doi":"10.1016/j.nicl.2023.103529","title":"Impact of follow ups, time interval and study duration in diffusion & myelin MRI clinical study in MS","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Philips (Canada); Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; CARE Canada; Q & T Research; Hôpital Fleurimont; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Centre Hospitalier Universitaire de Québec; Université de Sherbrooke","keywords":"Multiple sclerosis; Duration (music); Diffusion MRI; Medicine; White matter; Interval (graph theory); Confidence interval; Confounding; Affect (linguistics); Clinically isolated syndrome; Neurology; Internal medicine; Cardiology; Magnetic resonance imaging; Psychology; Radiology; Mathematics","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":[0.1672381,0.0008584699,0.001743516,0.0009027567,0.001736453,0.002088206,0.001043053,0.002473947,0.001830741],"category_scores_gemma":[0.2109544,0.0008087684,0.003194329,0.001651365,0.001689566,0.00206197,0.001704946,0.001372304,0.0002769167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007853999,"about_ca_system_score_gemma":0.001349562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006218677,"about_ca_topic_score_gemma":0.001118351,"domain_scores_codex":[0.8124843,0.1480504,0.01906197,0.01149294,0.00745212,0.001458308],"domain_scores_gemma":[0.675801,0.2492264,0.03640013,0.0273208,0.00641616,0.004835517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.227242,0.00243713,0.595199,0.001943843,0.01516209,0.0007115746,0.002031728,0.008980094,0.02200442,0.001933443,0.001077055,0.1212776],"study_design_scores_gemma":[0.005293051,0.04050764,0.9062235,0.0004951833,0.0114025,0.001121634,0.000421989,0.01281708,0.01064727,0.00508218,0.005694196,0.0002939178],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9439015,0.01310228,0.03753166,0.001500324,0.0005201304,0.0006191139,0.0009920961,0.0001375665,0.001695399],"genre_scores_gemma":[0.9833758,0.0004493452,0.01354852,0.000295626,0.0001605925,0.001249231,0.0005330252,0.0000529321,0.0003348974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1672381,"threshold_uncertainty_score":0.8844503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.212553186826201,"score_gpt":0.5221445582839719,"score_spread":0.3095913714577709,"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."}}