{"id":"W4378214502","doi":"10.32920/23159873","title":"Let's Get Physical: Exploring Gamification in Fitness Apps to Sustain User Engagement","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Toronto Metropolitan University","funders":"","keywords":"Artifact (error); Computer science; Download; Game design; Mobile apps; Odds; Video game; Game mechanics; Multimedia; Human–computer interaction; World Wide Web; Internet privacy; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002627811,0.0007204872,0.0002746953,0.001025386,0.001476152,0.005674604,0.001130147,0.001286264,0.004700631],"category_scores_gemma":[0.007599031,0.0002282067,0.0006466989,0.0004569273,0.002120001,0.004350056,0.005415089,0.001446935,0.001321535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007624199,"about_ca_system_score_gemma":0.001217701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078424,"about_ca_topic_score_gemma":0.002512154,"domain_scores_codex":[0.9982104,0.001216005,0.00003886432,0.00014123,0.000185766,0.0002076702],"domain_scores_gemma":[0.9973908,0.001966022,0.00008941677,0.0001288965,0.0001463964,0.0002784975],"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":[0.0006475409,0.003812089,0.02354275,0.003440879,0.0001260841,0.001640555,0.1723219,0.002631377,0.01009454,0.1034139,0.02425591,0.6540724],"study_design_scores_gemma":[0.0006424424,0.00514578,0.04215818,0.006962805,0.0005498768,0.00326052,0.2044813,0.04669401,0.01128002,0.2033284,0.4751274,0.0003694176],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6704317,0.003828157,0.1304443,0.01424456,0.0006258753,0.002331167,0.0001703379,0.001333155,0.1765908],"genre_scores_gemma":[0.88569,0.002165351,0.0954477,0.001792554,0.00006287157,0.001343179,0.0001260245,0.0001525392,0.01321977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005674604,"threshold_uncertainty_score":0.0157252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3024033897018266,"score_gpt":0.4979095932641401,"score_spread":0.1955062035623135,"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."}}