{"id":"W3120451003","doi":"10.1101/2020.12.29.20249002","title":"Sociodemographic Characteristics of Missing Data in Digital Phenotyping","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health; National Institutes of Health; National Institute on Drug Abuse; Harvard Catalyst","keywords":"Data collection; Global Positioning System; Computer science; Android (operating system); Accelerometer; Mobile device; Data science; World Wide Web; Statistics; Telecommunications; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005003578,0.0002478743,0.0005942169,0.0002659692,0.00003473102,0.0001519666,0.0009866168,0.0002880862,0.0002585129],"category_scores_gemma":[0.0002738987,0.0002888897,0.0001767724,0.0002530111,0.0001513455,0.0002424899,0.001843696,0.0007367611,0.00004778092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006629417,"about_ca_system_score_gemma":0.0001231721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000121085,"about_ca_topic_score_gemma":0.00004686539,"domain_scores_codex":[0.9974504,0.0001010678,0.001085894,0.0007521239,0.0002332968,0.0003772544],"domain_scores_gemma":[0.9974154,0.0001507926,0.000522867,0.001724332,0.0000786126,0.0001080189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006955721,0.002067096,0.6257783,0.002425165,0.0003045886,0.000352238,0.001913981,0.000001196563,0.00004450027,0.001912116,0.0002620445,0.3648692],"study_design_scores_gemma":[0.0005940259,0.00007278003,0.9831527,0.00513972,0.00007437697,0.00003851455,0.0007355016,0.0003678139,0.00006217128,0.008183768,0.0009941445,0.0005844838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985666,0.001311996,0.001139336,0.0004901062,0.003275575,0.0002964979,0.001332881,0.0000535186,0.006434053],"genre_scores_gemma":[0.9970862,0.00001192543,0.0003887072,0.00007545301,0.00011573,0.00002923193,0.001985672,0.00004866426,0.0002583881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3642848,"threshold_uncertainty_score":0.9999563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09313956209018044,"score_gpt":0.3929763313160353,"score_spread":0.2998367692258548,"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."}}