{"id":"W4416267655","doi":"10.2196/80094","title":"Exploring Age-Related Patterns in Smartphone Keystroke Dynamics Considering Temporal Variability: Cross-Sectional Study With AI-Based Analysis","year":2025,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Keystroke dynamics; Personalization; Keystroke logging; Dynamics (music); Behavioral analysis; Behavioral pattern; Mobile device; Smartphone application","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":[0.001434099,0.0003861355,0.0003843038,0.0008541906,0.0004628995,0.0006368528,0.0003306091,0.0004484263,0.001251303],"category_scores_gemma":[0.002796543,0.0002985354,0.0006137418,0.0007174535,0.0002310163,0.000733418,0.0004875661,0.0005213259,0.0003936148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229242,"about_ca_system_score_gemma":0.0003438223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003548142,"about_ca_topic_score_gemma":0.00501869,"domain_scores_codex":[0.9993793,0.0001569535,0.0000903832,0.0002254577,0.00007789959,0.00006999363],"domain_scores_gemma":[0.9986923,0.000258491,0.0003434974,0.0001887594,0.0003884426,0.0001284653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002097381,0.0002076016,0.9906014,0.00006337496,0.0001350362,0.0001366692,0.0006384784,0.0001199046,0.0008991251,0.00006824534,0.0003580267,0.006562255],"study_design_scores_gemma":[0.000009270047,0.0003057967,0.9963486,0.00002213961,0.0001069546,0.000284631,0.0007274874,0.001098536,0.0002435319,0.00008377566,0.0007562271,0.00001293064],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969785,0.0003287054,0.001488466,0.00003565935,0.00001648693,0.00008403473,0.0006164075,0.000009920781,0.0004418908],"genre_scores_gemma":[0.9972157,0.0001741962,0.00133339,0.00004792026,0.00002203087,0.0001311901,0.0007551432,0.000006687697,0.0003137703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003548142,"threshold_uncertainty_score":0.007584333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0672433571440588,"score_gpt":0.3805238976804522,"score_spread":0.3132805405363934,"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."}}