{"id":"W4282915382","doi":"10.2196/34366","title":"Fairness in Mobile Phone–Based Mental Health Assessment Algorithms: Exploratory Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mental health; Machine learning; Mobile phone; Computer science; Artificial intelligence; Algorithm; Applied psychology; Psychology; Psychiatry","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":[0.05169918,0.0004177892,0.0005746523,0.000953212,0.0009048359,0.001604046,0.001174581,0.0009967283,0.001264648],"category_scores_gemma":[0.2196565,0.0003785592,0.001141184,0.0006823227,0.001344515,0.002125237,0.001626665,0.001382188,0.0004338177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320461,"about_ca_system_score_gemma":0.001026199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002349808,"about_ca_topic_score_gemma":0.00198466,"domain_scores_codex":[0.9662933,0.02398033,0.002129406,0.002283761,0.004515017,0.0007981645],"domain_scores_gemma":[0.7380843,0.2228317,0.01210608,0.01115792,0.01466427,0.001155821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002668407,0.003359186,0.8841285,0.0004684697,0.0005693723,0.0002229447,0.01021882,0.01091008,0.001342183,0.002083021,0.001516391,0.08251259],"study_design_scores_gemma":[0.0004158467,0.01237961,0.6593459,0.0005911744,0.0007052653,0.00106134,0.01188551,0.2893109,0.01154093,0.005572406,0.006963607,0.0002275789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924535,0.0001743221,0.00594377,0.00012997,0.00001812273,0.0003694897,0.00009887312,0.00002684319,0.0007851233],"genre_scores_gemma":[0.9922768,0.00004677953,0.007116875,0.00007320059,0.00002355486,0.0001418067,0.0001078629,0.00001647802,0.0001967423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05169918,"threshold_uncertainty_score":0.2734147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1405733750715703,"score_gpt":0.5564156742757153,"score_spread":0.4158422992041449,"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."}}