{"id":"W4286545304","doi":"10.2196/34768","title":"Digital Biomarkers for Well-being Through Exergame Interactions: Exploratory Study","year":2022,"lang":"en","type":"article","venue":"JMIR Serious Games","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytics; Computer science; Set (abstract data type); Applied psychology; Test (biology); Categorization; Exploratory research; Human–computer interaction; Population; Digital health; Game play; Data science; Psychology; Artificial intelligence; Medicine; Health care","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":[0.003102095,0.0006719336,0.0005915133,0.000988376,0.0007232546,0.0009761336,0.0005710016,0.0006526143,0.002910726],"category_scores_gemma":[0.00959611,0.0003755798,0.0009501983,0.0005982555,0.0006088835,0.0007267382,0.00107893,0.0008038327,0.0009659836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004304849,"about_ca_system_score_gemma":0.000858101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001769743,"about_ca_topic_score_gemma":0.002718832,"domain_scores_codex":[0.9985377,0.000688106,0.0001003788,0.0002383522,0.0002459694,0.0001895553],"domain_scores_gemma":[0.9941025,0.003024264,0.001095674,0.000432872,0.0007793562,0.0005653498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001982122,0.01708227,0.9172072,0.0008639578,0.0005726118,0.0007615808,0.0136721,0.0006648237,0.002661457,0.0005107205,0.001202826,0.04281834],"study_design_scores_gemma":[0.0001282217,0.008437496,0.9791076,0.000123959,0.0002373657,0.0005483947,0.006603507,0.001688357,0.0008792722,0.0003467462,0.001858582,0.00004053976],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978079,0.00007137065,0.0007117198,0.00001959157,0.000003472877,0.0005690727,0.0002854467,0.00000803564,0.0005234524],"genre_scores_gemma":[0.9948384,0.00009962167,0.002317019,0.00006626192,0.0000128534,0.001454903,0.0004314721,0.000006812627,0.0007726598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003102095,"threshold_uncertainty_score":0.01640564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01788358986819251,"score_gpt":0.3152316648872172,"score_spread":0.2973480750190247,"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."}}