{"id":"W2041584768","doi":"10.1097/00004356-200023030-00009","title":"What government, agencies, and organizations can do to improve access to computers for postsecondary students with disabilities","year":2000,"lang":"en","type":"article","venue":"International Journal of Rehabilitation Research","topic":"Disability Education and Employment","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dawson College","funders":"","keywords":"Government (linguistics); Variety (cybernetics); Postsecondary education; Perspective (graphical); Psychology; Universal design; Medical education; Public relations; Higher education; Computer science; Political science; World Wide Web; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002256298,0.00008183303,0.0001291824,0.0001920695,0.000300643,0.001500981,0.0007908856,0.00003363327,0.0008178737],"category_scores_gemma":[0.003544353,0.00007211223,0.00004074596,0.0004535229,0.0003275008,0.001011831,0.000101075,0.0001204392,0.00001183232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001195478,"about_ca_system_score_gemma":0.0006088108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003787139,"about_ca_topic_score_gemma":0.001736945,"domain_scores_codex":[0.9968254,0.0002601639,0.0003667467,0.0002225681,0.00209046,0.00023467],"domain_scores_gemma":[0.9948527,0.001995832,0.00007354151,0.0001327202,0.002614167,0.0003310249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.001162125,0.001036091,0.3870421,0.00006343756,0.0002380216,0.00000230858,0.3830586,0.000843347,0.0002379643,0.009113754,0.03281082,0.1843913],"study_design_scores_gemma":[0.00152414,0.002537669,0.1613465,0.0003694184,0.00001792173,0.000005812573,0.6229082,0.00002285455,0.000144905,0.00553515,0.2053051,0.0002823795],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9063077,0.00002248352,0.0002442258,0.09126766,0.000739813,0.00085582,0.00004932576,0.000008013569,0.0005049811],"genre_scores_gemma":[0.9928631,0.00008339724,0.002957537,0.001076697,0.0002973426,0.00008419553,0.000005813982,0.00001304795,0.002618892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2398496,"threshold_uncertainty_score":0.9995356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04955546890004024,"score_gpt":0.4641557743310987,"score_spread":0.4146003054310584,"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."}}