{"id":"W1536360129","doi":"10.4018/978-1-59904-871-0.ch036","title":"Designing Mobile Technologies for Individuals with Disabilities","year":2008,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of British Columbia","funders":"","keywords":"Process (computing); Set (abstract data type); Assistive technology; Key (lock); Computer science; Domain (mathematical analysis); Universal design; Process management; Human–computer interaction; Data science; Knowledge management; Engineering; World Wide Web; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009235294,0.0006428117,0.0002911918,0.001010713,0.0008844323,0.003074877,0.0007241274,0.001428312,0.008572442],"category_scores_gemma":[0.001719264,0.0002219285,0.0003264846,0.0008362198,0.001087494,0.003182208,0.00173916,0.0007587564,0.003331749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008149247,"about_ca_system_score_gemma":0.0009038829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007893788,"about_ca_topic_score_gemma":0.00193214,"domain_scores_codex":[0.9995489,0.0002055558,0.00003397726,0.00004193836,0.0001268015,0.00004293834],"domain_scores_gemma":[0.9996362,0.0002486921,0.00001939732,0.0000235612,0.00004054285,0.00003166877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001735854,0.0000949121,0.001800597,0.002259028,0.000020567,0.0009076416,0.03740186,0.001192485,0.008035947,0.1510587,0.04557238,0.7516384],"study_design_scores_gemma":[0.00001085609,0.0001356428,0.002530986,0.001912579,0.00002687877,0.002146765,0.01437661,0.0006827048,0.001816325,0.03473781,0.9415979,0.00002491761],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06831214,0.08429074,0.2060809,0.01114524,0.00102856,0.001075187,0.0004337167,0.001145194,0.6264883],"genre_scores_gemma":[0.2281017,0.1343123,0.3124969,0.003935934,0.0004165284,0.002191059,0.0006417424,0.0005588603,0.317345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008572442,"threshold_uncertainty_score":0.02867764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02729631507053486,"score_gpt":0.279565910265073,"score_spread":0.2522695951945382,"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."}}