{"id":"W4403334207","doi":"10.2196/55170","title":"Measuring Environmental and Behavioral Drivers of Chronic Diseases Using Smartphone-Based Digital Phenotyping: Intensive Longitudinal Observational mHealth Substudy Embedded in 2 Prospective Cohorts of Adults","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Environmental Health Sciences; National Heart, Lung, and Blood Institute","keywords":"mHealth; Data collection; Observational study; Medicine; Sitting; Digital health; Applied psychology; Environmental health; Psychology; Psychological intervention; Health care; Nursing","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":[0.003169682,0.0006699663,0.0007050618,0.00106856,0.001690626,0.00109108,0.0007717266,0.001166237,0.001047684],"category_scores_gemma":[0.00351991,0.0007625729,0.001242595,0.001441095,0.0004389278,0.0008985958,0.001787308,0.001129667,0.0008530359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008242905,"about_ca_system_score_gemma":0.001248628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03120419,"about_ca_topic_score_gemma":0.04876139,"domain_scores_codex":[0.9984363,0.0005181434,0.0002412245,0.0003779345,0.0001895519,0.0002367436],"domain_scores_gemma":[0.9969857,0.0002451066,0.000830112,0.0008088756,0.000669085,0.0004610546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001216649,0.0008498807,0.9886425,0.0000990612,0.0004070808,0.0001141544,0.0006859017,0.0001504122,0.0008560985,0.00003830585,0.00152673,0.005413305],"study_design_scores_gemma":[0.0001491278,0.0007090006,0.996971,0.00003798225,0.0001883382,0.0001099945,0.0003763094,0.0002635513,0.0002218997,0.00003782039,0.000915567,0.00001937523],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880477,0.000251473,0.001330152,0.0001373994,0.00003962412,0.001020013,0.008407648,0.00004341155,0.000722566],"genre_scores_gemma":[0.9724806,0.0003813636,0.003931993,0.0004444955,0.0001020377,0.005736704,0.01579201,0.00002008745,0.0011107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03120419,"threshold_uncertainty_score":0.06204516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1057300159567865,"score_gpt":0.3919619188417056,"score_spread":0.2862319028849191,"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."}}