{"id":"W7103151465","doi":"10.30481/lis.2025.495292.2222","title":"Experience of Visually Impaired Users Interacting with Systems of the Iranian Research Institute for Information Science and Technology (IranDoc): Challenges and Limitations","year":2025,"lang":"fa","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Screen reader; Visually impaired; Software; Cursor (databases); Qualitative research; Legibility; Population; Reading (process)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.006057013,0.0002097571,0.0006440573,0.001651813,0.001113307,0.001991511,0.00302153,0.0001238987,0.00001430174],"category_scores_gemma":[0.0142332,0.0001556938,0.00007026507,0.004104301,0.008802952,0.01553789,0.001535684,0.0003160498,2.217086e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000226318,"about_ca_system_score_gemma":0.001423296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003155045,"about_ca_topic_score_gemma":0.003086759,"domain_scores_codex":[0.9963905,0.0002995275,0.001152589,0.0003983466,0.00131187,0.0004471975],"domain_scores_gemma":[0.9924745,0.002326686,0.001152991,0.0004495728,0.003466931,0.0001293027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001095662,0.0006336677,0.5979951,0.005147459,0.0003502562,0.000001159481,0.1507243,0.0001600691,0.01244018,0.07666911,0.000296939,0.1544861],"study_design_scores_gemma":[0.001731282,0.0001948716,0.4970306,0.009756844,0.0001357616,0.000006420039,0.4593183,0.000554674,0.01254943,0.01377815,0.004450292,0.0004933047],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977182,0.00997209,0.00003426651,0.0009970412,0.0005534284,0.001932202,0.00005720604,0.00001556587,0.009256208],"genre_scores_gemma":[0.991951,0.007718133,0.0000863897,0.0000172666,0.00001820466,0.0001325788,0.000001254553,0.000009027339,0.00006608987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.308594,"threshold_uncertainty_score":0.9990445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4066006520567035,"score_gpt":0.5880700870599891,"score_spread":0.1814694350032856,"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."}}