{"id":"W4293551514","doi":"","title":"SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Assistive technology; Computer science; Speech recognition; Human–computer interaction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.006727828,0.0003123422,0.0004008429,0.0001785527,0.0006013418,0.001294869,0.001259047,0.0004510206,0.00002381249],"category_scores_gemma":[0.01487349,0.0003087459,0.0001449155,0.0003377982,0.001395166,0.0003851267,0.001262495,0.0005087489,0.00001216364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003930177,"about_ca_system_score_gemma":0.0006735396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0018736,"about_ca_topic_score_gemma":0.01464223,"domain_scores_codex":[0.9962265,0.001499042,0.0003988539,0.0008646434,0.0005646539,0.0004463129],"domain_scores_gemma":[0.9938114,0.002095794,0.0004214026,0.00117633,0.002338566,0.0001565219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005161879,0.0007171095,0.004234609,0.0005293434,0.00006151827,0.000002477608,0.07660595,0.00001264058,0.00005111388,0.07085448,0.003701986,0.8431771],"study_design_scores_gemma":[0.002587497,0.000007434502,0.00579152,0.01754705,0.000318363,0.000008000355,0.2846335,0.007465617,0.01982283,0.5578498,0.1000718,0.003896589],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4346338,0.006297836,0.01070207,0.05153312,0.0004755066,0.002796641,0.000485602,0.001956587,0.4911188],"genre_scores_gemma":[0.9671898,0.0002435778,0.01536821,0.00004152489,0.00003991979,0.0002151645,0.0002125136,0.0000412201,0.01664808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8392805,"threshold_uncertainty_score":0.9999365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03395030435659022,"score_gpt":0.3188606489637678,"score_spread":0.2849103446071775,"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."}}