{"id":"W4379376248","doi":"10.2196/42750","title":"Knowledge Discovery in Ubiquitous and Personal Sleep Tracking: Scoping Review","year":2023,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Context (archaeology); Scopus; Sleep (system call); Computer science; Wearable computer; Tracking (education); Data science; mHealth; BitTorrent tracker; Activity tracker; Wearable technology; Health informatics; World Wide Web; Psychology; Eye tracking; MEDLINE; Health care; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001375632,0.0001729651,0.0004607193,0.0002663192,0.000212783,0.0001540445,0.0001940347,0.00007278688,0.000003958796],"category_scores_gemma":[0.00007555952,0.0001656456,0.00003929959,0.0008703736,0.00004645245,0.0008188514,0.0001744434,0.0002627966,0.00004301264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009288974,"about_ca_system_score_gemma":0.0005009341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001222824,"about_ca_topic_score_gemma":0.0005557741,"domain_scores_codex":[0.9978722,0.0002945927,0.0004877684,0.0005717211,0.0002160648,0.0005576588],"domain_scores_gemma":[0.998837,0.0003761795,0.0001699609,0.0002389671,0.00005330677,0.0003246174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002331302,0.0001405516,0.01089423,0.05282248,0.000008246854,0.00004564603,0.007579736,4.288665e-7,0.00001910581,0.001133183,0.002283737,0.9250494],"study_design_scores_gemma":[0.006610323,0.001550202,0.7456258,0.1842364,0.00007631275,0.001021179,0.00183118,0.04375319,0.00006064988,0.001851841,0.01089063,0.002492283],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8392803,0.1320372,0.005748107,0.01643207,0.001226273,0.003493437,0.00002430162,0.0006169366,0.001141396],"genre_scores_gemma":[0.9766527,0.02109816,0.00009838199,0.00170242,0.0001486124,0.0001552392,0.000006931054,0.00001406875,0.0001235052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9225571,"threshold_uncertainty_score":0.675483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1264462894348078,"score_gpt":0.4133676152558068,"score_spread":0.2869213258209989,"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."}}