{"id":"W2788690098","doi":"10.2196/humanfactors.8620","title":"Supporting Accurate Interpretation of Self-Administered Medical Test Results for Mobile Health: Assessment of Design, Demographics, and Health Condition","year":2018,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Respondent; Context (archaeology); Test (biology); Health care; Interpretation (philosophy); Applied psychology; Computer science; Medicine; Psychology; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.004560313,0.0002164702,0.0006820765,0.0003181015,0.001164568,0.000007824175,0.0002047321,0.0002722551,0.00008865266],"category_scores_gemma":[0.0005011013,0.0001971576,0.00007988791,0.000312551,0.0002280688,0.0001245797,0.00007090208,0.0004283293,0.000002742044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000247893,"about_ca_system_score_gemma":0.002987458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002492008,"about_ca_topic_score_gemma":0.0007224577,"domain_scores_codex":[0.9950265,0.0005867501,0.002712773,0.000460589,0.0004488181,0.0007645566],"domain_scores_gemma":[0.9931916,0.002037912,0.003058179,0.0003974651,0.0005713725,0.0007434962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008952451,0.003617309,0.6835577,0.03242552,0.0002165806,0.000001257644,0.05898937,0.000009956943,0.001130947,0.02221185,0.1394033,0.05754086],"study_design_scores_gemma":[0.01007704,0.02539183,0.8888299,0.003402288,0.000064489,0.000004175216,0.01053799,0.009380041,0.0004350945,0.002336989,0.04888808,0.0006520096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8925097,0.0003485522,0.05113126,0.006139028,0.0009594993,0.04476182,0.002823347,0.0004472662,0.0008795313],"genre_scores_gemma":[0.9865056,0.0001640596,0.003392207,0.001298853,0.0001608821,0.007592082,0.0007944733,0.00003291557,0.00005890784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2052722,"threshold_uncertainty_score":0.8957036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130657593795472,"score_gpt":0.5435450752538624,"score_spread":0.4304793158743152,"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."}}