{"id":"W4403218269","doi":"10.2196/62959","title":"Developing a Sleep Algxorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study","year":2024,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Sleep and related disorders","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Observational study; Sleep (system call); Algorithm; Computer science; Medicine; World Wide Web; Operating system; Internal 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":[0.004371305,0.0006096172,0.0006155144,0.0005202177,0.001010549,0.0009577232,0.0008046719,0.000851971,0.001790201],"category_scores_gemma":[0.01125091,0.0004954663,0.001071143,0.0004416775,0.0005167435,0.001266371,0.000686666,0.001480868,0.0008078318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009266483,"about_ca_system_score_gemma":0.001596633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003707154,"about_ca_topic_score_gemma":0.005986067,"domain_scores_codex":[0.9977242,0.0009957597,0.0002891286,0.0003865001,0.000413292,0.0001909947],"domain_scores_gemma":[0.9935514,0.001367517,0.001916846,0.0008522529,0.001479702,0.0008323449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02904162,0.1209258,0.7743986,0.0006402804,0.001653462,0.0002550145,0.003057681,0.0003936517,0.002818377,0.0002650573,0.003382086,0.0631685],"study_design_scores_gemma":[0.008318049,0.1527844,0.8276408,0.0001198668,0.0007702201,0.0002651491,0.00224195,0.002557371,0.001076378,0.0002124054,0.003929708,0.00008374989],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971535,0.00007848871,0.0006300298,0.00009322454,0.00002501027,0.001156242,0.0004265117,0.00001949774,0.0004175077],"genre_scores_gemma":[0.9896124,0.0001386336,0.00367368,0.0005887091,0.00008265286,0.003663448,0.001316029,0.00001954979,0.0009048338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004371305,"threshold_uncertainty_score":0.0231179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06562230576364632,"score_gpt":0.41595563122638,"score_spread":0.3503333254627337,"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."}}