{"id":"W3212526843","doi":"10.2196/31618","title":"Identifying Data Quality Dimensions for Person-Generated Wearable Device Data: Multi-Method Study","year":2021,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health","keywords":"Data quality; Wearable computer; Computer science; Wearable technology; Focus group; Quality (philosophy); Data science; Data collection; Facilitator; Psychology; Engineering; Metric (unit)","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2446788,0.001363039,0.005052891,0.01226397,0.002357518,0.006061807,0.002945058,0.002483369,0.00416518],"category_scores_gemma":[0.368612,0.001582054,0.008875025,0.01366878,0.002885906,0.005712561,0.005077081,0.001844347,0.0005065548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006733614,"about_ca_system_score_gemma":0.01361995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003214839,"about_ca_topic_score_gemma":0.006413653,"domain_scores_codex":[0.7245936,0.1659809,0.06080608,0.01380005,0.03199289,0.002826433],"domain_scores_gemma":[0.4972754,0.3847189,0.04694916,0.01792279,0.05144142,0.001692364],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.004538407,0.002352061,0.2944442,0.2559648,0.03050373,0.002343463,0.1021837,0.001708727,0.002562599,0.00949507,0.005441707,0.2884615],"study_design_scores_gemma":[0.00517874,0.01362274,0.350738,0.2441541,0.07171786,0.005075115,0.1683659,0.01435188,0.009842511,0.02170896,0.09385016,0.00139415],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4930412,0.1528762,0.20819,0.004936036,0.0009748937,0.123284,0.005798814,0.0003987673,0.0105001],"genre_scores_gemma":[0.7114533,0.0129046,0.1401496,0.002176699,0.0001987237,0.1308495,0.001195505,0.0001194001,0.0009528315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7553212,"threshold_uncertainty_score":0.9314455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5775762664505723,"score_gpt":0.6179330072792392,"score_spread":0.04035674082866691,"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."}}