{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00475965,0.0001829631,0.0003205033,0.0009216729,0.0008857358,0.00007046514,0.0005563546,0.00003574301,0.002941095],"category_scores_gemma":[0.000007596515,0.0001913223,0.00009629976,0.00147506,0.0001486573,0.0004569099,0.00067636,0.001284275,0.0005578076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003193732,"about_ca_system_score_gemma":0.0004922245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003793174,"about_ca_topic_score_gemma":0.0002537321,"domain_scores_codex":[0.9928201,0.003399325,0.0007866588,0.0004655952,0.001503673,0.001024611],"domain_scores_gemma":[0.9987646,0.0002169507,0.000165812,0.0004903532,0.0001069905,0.000255286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001359358,0.1178681,0.01800866,0.000622642,0.0002486644,0.0002971939,0.405204,0.0001686469,0.00002376932,0.006386827,0.1867397,0.2630725],"study_design_scores_gemma":[0.009477166,0.03053932,0.09973053,0.0001671601,0.000002390012,0.0000196698,0.8148088,0.00139712,0.00007073006,0.001026416,0.0422728,0.0004878471],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777924,0.0003639901,0.0001465531,0.001773446,0.001849677,0.00641536,0.000673218,0.0001071447,0.01087819],"genre_scores_gemma":[0.975176,0.00000180143,0.00005439294,0.000214697,0.0000280852,0.02341894,0.0001670901,0.00003628205,0.0009026792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4096048,"threshold_uncertainty_score":0.9979703,"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."}}