{"id":"W4413900557","doi":"10.1016/j.ipm.2025.104386","title":"Zoning out in health management: Exploring information non-behaviour among older Chinese immigrants with diabetes in Canada","year":2025,"lang":"en","type":"article","venue":"Information Processing & Management","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"China Scholarship Council; Fonds de Recherche du Québec-Société et Culture; McGill University","keywords":"Zoning; Immigration; Diabetes mellitus; Gerontology; Diabetes management; Medicine; Geography; Political science; Type 2 diabetes; Archaeology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002136367,0.000330811,0.0004439912,0.001444085,0.0007308561,0.0001816114,0.0003779332,0.0000889873,0.00005421215],"category_scores_gemma":[0.00005383123,0.0002835931,0.00003067729,0.001462866,0.00003097373,0.01531759,0.0002297255,0.0006898177,0.00006025942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002498401,"about_ca_system_score_gemma":0.00120143,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1638414,"about_ca_topic_score_gemma":0.3179835,"domain_scores_codex":[0.9945387,0.0001618012,0.003486115,0.0002211441,0.0006232649,0.0009689757],"domain_scores_gemma":[0.9978428,0.00007018038,0.001305951,0.0003967036,0.0002338039,0.0001505844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000048478,0.00003059225,0.820658,0.01158488,0.000014291,0.000001482409,0.0178622,0.001715808,3.492299e-8,0.0002512489,0.0005451518,0.1472878],"study_design_scores_gemma":[0.002450993,0.00001303253,0.929955,0.005777289,0.000007951367,8.540329e-8,0.02991241,0.02458143,0.000002036842,0.00008502488,0.00695972,0.0002550224],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9490322,0.00004724948,0.007930741,0.0008579005,0.0006748788,0.003429731,0.00001708658,0.0001346701,0.03787553],"genre_scores_gemma":[0.9882403,0.00005938012,0.00150264,0.008010673,0.00001547428,0.001658718,0.0002231123,0.00001097388,0.0002787535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1541421,"threshold_uncertainty_score":0.9999616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646584215884741,"score_gpt":0.3360500034826462,"score_spread":0.3195841613237988,"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."}}