{"id":"W2132622541","doi":"","title":"Digital Technology, Learning, and Postsecondary Students with Disabilities: Where We've Been and Where We're Going.","year":2014,"lang":"en","type":"article","venue":"The Journal of Postsecondary Education and Disability","topic":"Disability Education and Employment","field":"Social Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Postsecondary education; Assistive technology; ICTS; Emerging technologies; Psychology; Universal design; Information and Communications Technology; Educational technology; Higher education; Learning disability; Universal Design for Learning; Pedagogy; Engineering ethics; Computer science; Political science; Engineering; World Wide Web; Developmental psychology; Human–computer interaction","routes":{"ca_aff":false,"ca_fund":false,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.00189077,0.0002304441,0.0003438672,0.00008066214,0.000762513,0.0004220977,0.0003493326,0.0001358637,0.0007763015],"category_scores_gemma":[0.0008762795,0.0001603286,0.00005798597,0.0002224473,0.003189395,0.0008364893,0.000136625,0.0005000619,0.000008747233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001917468,"about_ca_system_score_gemma":0.0005472838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001734406,"about_ca_topic_score_gemma":0.002229484,"domain_scores_codex":[0.9979194,0.0004965761,0.000528294,0.0003019797,0.0004504767,0.0003032945],"domain_scores_gemma":[0.9978774,0.0008726104,0.0003354401,0.000282822,0.0002656906,0.0003660645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001230592,0.000732687,0.8295172,0.0002052077,0.00004678109,1.061444e-7,0.05253145,5.876925e-7,0.000008966356,0.001151978,0.002395332,0.1132866],"study_design_scores_gemma":[0.0007685457,0.0007828465,0.1387055,0.0003426705,0.00008637518,0.00006164141,0.5830208,0.000003931321,0.000009693861,0.007600433,0.2683222,0.0002953413],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9251571,0.004464835,0.000007818822,0.0637686,0.000264059,0.0004673425,0.00001504426,0.00003554377,0.00581972],"genre_scores_gemma":[0.9938434,0.002159852,0.0000824725,0.0003051729,0.0002175813,0.00001598134,0.000004582534,0.00001719236,0.003353713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6908118,"threshold_uncertainty_score":0.9995233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01128323796932497,"score_gpt":0.3173807514124606,"score_spread":0.3060975134431356,"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."}}