{"id":"W4413295453","doi":"10.2196/68345","title":"Automating Individualized Notification of Drug Recalls to Patients: Complex Challenges and Qualitative Evaluation","year":2025,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of California, San Francisco; U.S. Department of Health and Human Services","keywords":"Preprint; Qualitative research; Drug; Computer science; Medicine; World Wide Web; Pharmacology; Sociology","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":[0.1026841,0.0006320974,0.0009158711,0.002256461,0.00536134,0.004592987,0.002421689,0.001390586,0.00260676],"category_scores_gemma":[0.1274395,0.0005629073,0.0006227104,0.001804264,0.007224058,0.003469297,0.007457237,0.001806097,0.0004157075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01088677,"about_ca_system_score_gemma":0.01357712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006778526,"about_ca_topic_score_gemma":0.01168687,"domain_scores_codex":[0.8974171,0.08813526,0.002808732,0.002393346,0.005624821,0.003620768],"domain_scores_gemma":[0.820574,0.1486401,0.007045062,0.004293861,0.0167649,0.00268209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001139237,0.0002339393,0.01109679,0.001082902,0.00001723946,0.0003657359,0.9454925,0.0002029805,0.001212279,0.002238018,0.001656415,0.03628732],"study_design_scores_gemma":[0.00004858661,0.0002864313,0.007595717,0.001025263,0.0000250471,0.0001534534,0.9712325,0.0007814949,0.001830811,0.001911023,0.01505485,0.00005472104],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9498983,0.0007572277,0.02471411,0.006640303,0.0001367287,0.005528554,0.0008280826,0.0001270852,0.01136964],"genre_scores_gemma":[0.9627033,0.000566164,0.02348801,0.001940591,0.00003609896,0.008139313,0.0002867839,0.00008568668,0.002753984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1026841,"threshold_uncertainty_score":0.543052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2249843076344837,"score_gpt":0.5623899179541543,"score_spread":0.3374056103196705,"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."}}