{"id":"W2757174779","doi":"10.2196/iproc.8580","title":"Wearable Activity Trackers and Older Adults: The Social Effect and Importance in Healthcare","year":2017,"lang":"en","type":"article","venue":"Iproceedings","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Activity tracker; Physical activity; Health care; Gerontology; Wearable computer; Chronic disease; Wearable technology; Quality of life (healthcare); Medicine; Disease; Psychology; Physical therapy; Family medicine; Nursing; Computer science","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":[0.002884836,0.0002802323,0.0004036458,0.001421578,0.002120475,0.002758429,0.0003655423,0.001235304,0.002639448],"category_scores_gemma":[0.01076228,0.0002303859,0.0003972659,0.0009854556,0.002468899,0.003329338,0.003229763,0.001188775,0.0001905552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079923,"about_ca_system_score_gemma":0.0007722309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004702417,"about_ca_topic_score_gemma":0.008349088,"domain_scores_codex":[0.9974836,0.001691082,0.0001111999,0.0001904708,0.0003694423,0.0001543004],"domain_scores_gemma":[0.9923603,0.003961489,0.00161733,0.0002184189,0.0006142557,0.001228254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002243232,0.0003912142,0.4745905,0.001341177,0.0003508859,0.001505778,0.2399912,0.0001723421,0.001045681,0.007436441,0.01598563,0.2569648],"study_design_scores_gemma":[0.00003965413,0.0005652764,0.7228476,0.001909568,0.0001845908,0.002284695,0.1937553,0.0004195223,0.0001653416,0.007111012,0.07061075,0.0001066467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8691586,0.04649047,0.001494548,0.04244912,0.0007358398,0.00008338432,0.0002804466,0.00004104243,0.03926655],"genre_scores_gemma":[0.9804313,0.01421321,0.0004685693,0.003319936,0.0005163095,0.0000404789,0.00004855402,0.000009471733,0.0009520493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004702417,"threshold_uncertainty_score":0.01525664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02622877426883968,"score_gpt":0.415914473083299,"score_spread":0.3896856988144593,"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."}}