{"id":"W4366539480","doi":"10.2196/39442","title":"Aiding clinical decision-making at the individual and community level using mobile sensor data – A study protocol for an experimental design (Preprint)","year":2022,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Protocol (science); Computer science; Data science; Medicine; World Wide Web; Alternative medicine","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":[0.05097553,0.003582094,0.004112614,0.002586447,0.003829752,0.002648817,0.002500704,0.005266942,0.04575101],"category_scores_gemma":[0.05328946,0.002304991,0.003284886,0.003185786,0.002966131,0.001792731,0.002395957,0.004353296,0.01062859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003330711,"about_ca_system_score_gemma":0.01572497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001574519,"about_ca_topic_score_gemma":0.002187234,"domain_scores_codex":[0.964596,0.02274867,0.004575488,0.00205778,0.00359313,0.002428897],"domain_scores_gemma":[0.9676051,0.01051384,0.004569796,0.006790467,0.009098897,0.001421902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.4661109,0.1104586,0.006489099,0.03370374,0.001992343,0.001160767,0.00504059,0.009664678,0.01390106,0.02706082,0.06265609,0.2617614],"study_design_scores_gemma":[0.4144225,0.1984587,0.02728295,0.0150267,0.001482512,0.0003082419,0.00244989,0.01612953,0.01161712,0.01620911,0.2960504,0.0005623672],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.00201176,0.00006994471,0.003528259,0.00006974635,0.000193764,0.9928871,0.000483216,0.0000550083,0.0007012218],"genre_scores_gemma":[0.0006816632,0.00002255334,0.003202586,0.00003092084,0.000008277359,0.9958561,0.00003528863,0.000002345386,0.0001602457],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.05097553,"threshold_uncertainty_score":0.2695876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9038394727115536,"score_gpt":0.765789740112663,"score_spread":0.1380497325988906,"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."}}