{"id":"W4224280316","doi":"10.3389/fnhum.2022.841035","title":"Brain Computer Interfaces and Communication Disabilities: Ethical, Legal, and Social Aspects of Decoding Speech From the Brain","year":2022,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Healthcare Decision-Making and Restraints","field":"Psychology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto; Centre for Addiction and Mental Health; McGill University; University of Ottawa; Institute of Health Services and Policy Research; Queen's University","funders":"Canadian Institutes of Health Research","keywords":"Harm; Agency (philosophy); Decoding methods; Brain–computer interface; Psychology; Interface (matter); Computer science; Perspective (graphical); Cognitive psychology; Internet privacy; Human–computer interaction; Social psychology; Artificial intelligence; Neuroscience; Sociology; Telecommunications; Electroencephalography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001281351,0.00009687945,0.0001895999,0.0000850037,0.0008133236,0.00007949243,0.0005710102,0.00007727087,0.00003939484],"category_scores_gemma":[0.000381493,0.00008168026,0.00002450082,0.0002051858,0.001258636,0.00006845706,0.0004224781,0.0008041329,1.99343e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004460737,"about_ca_system_score_gemma":0.00003527516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005435387,"about_ca_topic_score_gemma":0.0001175475,"domain_scores_codex":[0.997712,0.001123041,0.0003002772,0.0003896309,0.0002617553,0.0002133553],"domain_scores_gemma":[0.9980268,0.001456136,0.0001206046,0.0003421409,0.00001641004,0.00003785748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003353528,0.0008050118,0.07200098,0.0001334559,0.00003894663,0.0003089632,0.3734798,0.0004301659,0.01179783,0.08017229,0.1859549,0.2745423],"study_design_scores_gemma":[0.003190244,0.001746834,0.5633214,0.0003482608,0.00002736179,0.0003594133,0.1582895,0.01736284,0.0002442505,0.1687475,0.08529922,0.001063159],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977406,0.0002700766,0.002421015,0.0183352,0.0009788192,0.0001954879,0.00003195208,0.00001908379,0.0003423734],"genre_scores_gemma":[0.9945672,0.00001058257,0.0008815976,0.004383655,0.00004187955,0.00001371996,0.000002685004,0.000009123421,0.00008957523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4913204,"threshold_uncertainty_score":0.625551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05250592023375155,"score_gpt":0.3749431278680657,"score_spread":0.3224372076343142,"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."}}