{"id":"W3178658338","doi":"10.1177/15553434211029530","title":"Ecological Design of an Augmentative and Alternative Communication Device Interface","year":2021,"lang":"en","type":"article","venue":"Journal of Cognitive Engineering and Decision Making","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Fondation Brain Canada","keywords":"Augmentative and alternative communication; Computer science; Human–computer interaction; Interface (matter); Augmentative; Process (computing); Domain (mathematical analysis); User interface; Workload; Workspace; Psychology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001718227,0.0007627088,0.000249316,0.0009289145,0.001098488,0.001854543,0.001240471,0.0008070605,0.004894845],"category_scores_gemma":[0.003891368,0.0005067726,0.0005609206,0.0002609059,0.001331882,0.001181095,0.002481004,0.0004415024,0.0009392474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008200246,"about_ca_system_score_gemma":0.001468331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002775493,"about_ca_topic_score_gemma":0.003786112,"domain_scores_codex":[0.9988912,0.0005818476,0.00005851515,0.0001713716,0.0002090103,0.00008813778],"domain_scores_gemma":[0.9989516,0.0004671082,0.0000706849,0.00012615,0.0002324027,0.0001519795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001554262,0.003264788,0.04441176,0.001764672,0.0002233421,0.003336861,0.05484141,0.1448516,0.3326589,0.1262984,0.00457165,0.2822223],"study_design_scores_gemma":[0.0006203369,0.005013961,0.04060721,0.0003613214,0.0004157514,0.002390975,0.0176159,0.709641,0.06037224,0.060651,0.1019955,0.0003147546],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4051399,0.00009964133,0.5605237,0.0004792426,0.00007029985,0.001148869,0.0001751581,0.001704739,0.03065836],"genre_scores_gemma":[0.7258875,0.00006371935,0.2669244,0.00008636435,0.00001087099,0.000637696,0.00008987908,0.0001154892,0.006184063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004894845,"threshold_uncertainty_score":0.01637489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1110878445421994,"score_gpt":0.4709468004480844,"score_spread":0.359858955905885,"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."}}