{"id":"W3010254105","doi":"10.1145/3386402.3386409","title":"Design and evaluation of a context-adaptive AAC application for people with aphasia","year":2020,"lang":"en","type":"article","venue":"ACM SIGACCESS Accessibility and Computing","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Context (archaeology); Augmentative and alternative communication; Vocabulary; Aphasia; Augmentative; Human–computer interaction; Work (physics); Multimedia; Natural language processing; Linguistics; Cognitive psychology; Psychology","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":[0.002644923,0.001039568,0.0005278104,0.0006862238,0.000720229,0.000926564,0.001133014,0.001266382,0.002874105],"category_scores_gemma":[0.00606799,0.000367048,0.0004667206,0.0002438649,0.00054719,0.0007789755,0.0008756033,0.0004795753,0.0006576768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004695448,"about_ca_system_score_gemma":0.001218187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002049879,"about_ca_topic_score_gemma":0.002219118,"domain_scores_codex":[0.9982117,0.0009402686,0.0001882836,0.000202583,0.000317829,0.0001393689],"domain_scores_gemma":[0.9973967,0.001153498,0.0001107643,0.0001314629,0.0009185271,0.0002890784],"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":[0.008369258,0.01375368,0.01895363,0.00389495,0.0003604599,0.003810561,0.01870545,0.01848542,0.4196773,0.001572931,0.00367559,0.4887408],"study_design_scores_gemma":[0.009465966,0.1288602,0.09871623,0.001140384,0.002845498,0.005230638,0.01714812,0.2416029,0.4195851,0.003385089,0.07123106,0.0007887711],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8924925,0.0003272456,0.09197296,0.0002329137,0.0001007174,0.008215021,0.0002652381,0.001565596,0.004827849],"genre_scores_gemma":[0.7858217,0.00031031,0.2030334,0.0002278028,0.00003200604,0.005274026,0.0003198588,0.000159111,0.004821843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002874105,"threshold_uncertainty_score":0.0139879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1873265415395488,"score_gpt":0.4561251056966855,"score_spread":0.2687985641571367,"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."}}