{"id":"W2888870628","doi":"10.2196/11876","title":"Participant Engagement with a Hyper-Personalized Activity Tracking Smartphone App","year":2018,"lang":"en","type":"article","venue":"Iproceedings","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mobile apps; User engagement; Smartphone app; Physical activity; Tracking (education); Affect (linguistics); Activity tracker; Internet privacy; Computer science; Human–computer interaction; Psychology; World Wide Web; Medicine; Physical medicine and rehabilitation; Communication","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":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001446621,0.0002400006,0.0003910202,0.0001099821,0.002480003,0.00002072714,0.0002053532,0.0001765052,0.001038504],"category_scores_gemma":[0.0002267778,0.0001909223,0.00004804437,0.00050631,0.0002367598,0.0002236306,0.00008050302,0.0007763131,0.001014634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001975612,"about_ca_system_score_gemma":0.000634868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004606315,"about_ca_topic_score_gemma":0.0001958519,"domain_scores_codex":[0.9972131,0.0001133522,0.0005186272,0.0005483232,0.0003933051,0.001213259],"domain_scores_gemma":[0.9979687,0.0002702466,0.0003625709,0.000286146,0.0005127829,0.0005995614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005488623,0.001698557,0.1868535,0.005355699,0.0002729428,0.00001405365,0.119961,0.000001888596,0.05706998,0.06428459,0.2198534,0.3391457],"study_design_scores_gemma":[0.002914435,0.0005304152,0.04554193,0.0003719795,0.0000902553,0.000007380911,0.004529836,0.0002402997,0.001259972,0.0004035117,0.943766,0.0003440015],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728654,0.0001117393,0.001795297,0.005700546,0.0003482292,0.003187579,0.00001370632,0.0004764039,0.01550111],"genre_scores_gemma":[0.9806984,0.00009483637,0.00176899,0.00609477,0.00109539,0.008085631,0.000006916804,0.00005362526,0.002101444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7239125,"threshold_uncertainty_score":0.9998747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1679226354703559,"score_gpt":0.4449436999176173,"score_spread":0.2770210644472615,"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."}}