{"id":"W3002274972","doi":"10.1123/japa.2019-0244","title":"Considerations in Processing Accelerometry Data to Explore Physical Activity and Sedentary Time in Older Adults","year":2020,"lang":"en","type":"article","venue":"Journal of Aging and Physical Activity","topic":"Physical Activity and Health","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Office of the First Minister and Deputy First Minister; Queen's University; Health and Social Care Research and Development Division; Medical Research Council; Public Health Agency; Centre for Ageing Research and Development in Ireland; Queen's University Belfast; United Kingdom Clinical Research Collaboration; Wellcome Trust","keywords":"Physical activity; Sedentary behavior; Accelerometer; Psychology; Gerontology; Actigraphy; Medicine; Physical medicine and rehabilitation; Computer science; Psychiatry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001762283,0.0001715981,0.0007245803,0.0001214973,0.00007826115,0.00005162358,0.00008686849,0.00004486173,0.000004653403],"category_scores_gemma":[0.0001912754,0.0001426774,0.00005209542,0.0003719176,0.00007020437,0.001023666,0.0001818374,0.0008998939,0.000002799765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005883611,"about_ca_system_score_gemma":0.000152881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001064337,"about_ca_topic_score_gemma":0.0000152952,"domain_scores_codex":[0.9988362,0.0001137628,0.0001633536,0.0003513714,0.0002958588,0.0002395039],"domain_scores_gemma":[0.9988649,0.0003884085,0.000146792,0.0001503827,0.00005160224,0.0003978632],"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":[0.004285663,0.0278658,0.04563732,0.002533474,0.0001812733,0.0006299848,0.05620266,0.0001137341,0.3596331,0.00004111625,0.001009612,0.5018662],"study_design_scores_gemma":[0.00334901,0.001050159,0.9315538,0.001137973,0.00008742412,0.00008188841,0.0005340629,0.04766509,0.01382026,0.0004213759,0.00003000322,0.0002689007],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837064,0.00003717433,0.00008135767,0.01588264,0.00001672268,0.0002089929,0.00001443133,0.00001325246,0.00003904623],"genre_scores_gemma":[0.9986861,0.00001598506,0.0001867749,0.0005326908,0.000556051,0.000002662,0.000002698434,0.00001374188,0.000003322064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8859165,"threshold_uncertainty_score":0.5818215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1479253885426653,"score_gpt":0.3863377556891933,"score_spread":0.238412367146528,"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."}}