{"id":"W3030474364","doi":"10.1038/s41746-020-0286-7","title":"A data-driven framework for selecting and validating digital health metrics: use-case in neurological sensorimotor impairments","year":2020,"lang":"en","type":"article","venue":"npj Digital Medicine","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Staatssekretariat für Bildung, Forschung und Innovation; Canadian Institutes of Health Research; European Commission; James S. McDonnell Foundation","keywords":"Computer science; Set (abstract data type); Machine learning; Reliability (semiconductor); Artificial intelligence; Selection (genetic algorithm); Discriminant validity; Data mining; Physical medicine and rehabilitation; Psychometrics; Medicine; Mathematics; Statistics","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":[0.1108849,0.002785866,0.002443216,0.01203728,0.001767676,0.00928132,0.004916719,0.003506328,0.002768746],"category_scores_gemma":[0.2346524,0.001317553,0.003129482,0.006590887,0.003249577,0.005380126,0.007875235,0.00369298,0.001383707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003645407,"about_ca_system_score_gemma":0.008437154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008340647,"about_ca_topic_score_gemma":0.01055832,"domain_scores_codex":[0.9119233,0.05309841,0.01065379,0.007699902,0.01552657,0.001098023],"domain_scores_gemma":[0.7691829,0.162408,0.01359653,0.01903736,0.03349808,0.00227715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009464422,0.001448918,0.07108965,0.003480526,0.001164872,0.001607024,0.004502641,0.1362151,0.009014274,0.1031366,0.0139231,0.6534707],"study_design_scores_gemma":[0.000514418,0.001032087,0.01908534,0.002519292,0.0005373989,0.001303395,0.001498916,0.7503178,0.01820723,0.16328,0.04124057,0.000463513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00953146,0.0003961128,0.9828363,0.001062632,0.00003390041,0.001867369,0.001191544,0.001499207,0.001581458],"genre_scores_gemma":[0.09120704,0.0001512549,0.903525,0.0002732708,0.00003338801,0.002278456,0.002101014,0.0001899601,0.0002406238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1108849,"threshold_uncertainty_score":0.5864226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1247232285421485,"score_gpt":0.3723141976196553,"score_spread":0.2475909690775068,"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."}}