{"id":"W2475559403","doi":"10.4018/978-1-4666-4422-9.ch036","title":"Nascent Access Technologies for Individuals with Severe Motor Impairments","year":2013,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Exploit; Access technology; Face (sociological concept); Emerging technologies; Computer science; Instrumentation (computer programming); Neuroscience; Psychology; Human–computer interaction; Computer security; Telecommunications; Artificial intelligence; Sociology","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":[0.0002177729,0.0009229181,0.0003539925,0.0008853914,0.0004333051,0.001920143,0.000859803,0.001831633,0.02631927],"category_scores_gemma":[0.0005714279,0.0001951597,0.0003878355,0.0006550929,0.0009528225,0.003552212,0.001451673,0.001632787,0.0101434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005723076,"about_ca_system_score_gemma":0.0005902391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000556074,"about_ca_topic_score_gemma":0.001569423,"domain_scores_codex":[0.9998518,0.00001725487,0.000009802776,0.00003570623,0.00007041285,0.00001503103],"domain_scores_gemma":[0.9998462,0.00009441018,0.000007719093,0.00001094145,0.0000293424,0.00001137572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002970544,0.00004396033,0.0002068492,0.001464104,0.00001160439,0.0004617875,0.0009894824,0.0004576656,0.006967109,0.159944,0.07923383,0.7501898],"study_design_scores_gemma":[0.000004648407,0.00005283886,0.0006074643,0.001075664,0.00001090708,0.002445504,0.0002770642,0.0006217493,0.00207226,0.04918621,0.9436262,0.00001954952],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007761916,0.324522,0.1079308,0.008446297,0.004534479,0.0001660448,0.0005457383,0.001067057,0.5450256],"genre_scores_gemma":[0.03191629,0.284498,0.06067354,0.003922855,0.002231463,0.0002574239,0.0004788158,0.0002978411,0.6157238],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02631927,"threshold_uncertainty_score":0.08804673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03103916044990803,"score_gpt":0.282052420978446,"score_spread":0.251013260528538,"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."}}