{"id":"W4400522354","doi":"10.2196/54859","title":"Integrating Health and Disability Data Into Academic Information Systems: Workflow Optimization Study","year":2024,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Workflow; Computer science; Data science; Psychology; World Wide Web; Database","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00141155,0.000161634,0.0002206503,0.00009969367,0.0006806667,0.001539244,0.0005669807,0.0001013032,0.00003085694],"category_scores_gemma":[0.0007588285,0.0001344248,0.00003175757,0.000447287,0.0005005501,0.007069651,0.0003254355,0.0003005862,0.000009814091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005690376,"about_ca_system_score_gemma":0.0002067209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00618535,"about_ca_topic_score_gemma":0.003715918,"domain_scores_codex":[0.997908,0.0002967463,0.0006042113,0.0003891321,0.0005386314,0.0002632619],"domain_scores_gemma":[0.99889,0.0002715412,0.0001240195,0.0004591631,0.00006050145,0.0001947148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.000007414123,0.0001778386,0.4933006,0.0007568731,0.00003419233,2.182579e-7,0.4609263,0.0002186335,5.551083e-7,0.01971403,0.000794858,0.02406847],"study_design_scores_gemma":[0.0001969804,0.0002754878,0.03029409,0.0004449099,0.00001874314,2.446256e-7,0.9458766,0.006352711,5.916556e-7,0.005457692,0.01066422,0.0004177214],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941543,0.0003751667,0.000254992,0.0002706277,0.000408135,0.001587771,0.00005778426,0.000422306,0.002468952],"genre_scores_gemma":[0.999259,0.00001584335,0.00007022743,0.00002585161,0.0001169316,0.00006201812,0.0003509052,0.00001088731,0.00008836148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4849503,"threshold_uncertainty_score":0.9994972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08013598042247123,"score_gpt":0.4180533183665051,"score_spread":0.3379173379440338,"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."}}