{"id":"W3163756696","doi":"10.1109/icse43902.2021.00143","title":"Semantic Web Accessibility Testing via Hierarchical Visual Analysis","year":2021,"lang":"en","type":"article","venue":"","topic":"Digital Accessibility for Disabilities","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; USable; Semantic Web; Social Semantic Web; World Wide Web; Web accessibility; Inference; Process (computing); Web testing; Semantic analytics; Globe; Semantic Web Stack; Data Web; Web standards; Information retrieval; Data science; Web page; Web modeling; Artificial intelligence; Web intelligence; Programming language","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00123141,0.0001638573,0.0003843419,0.0001332491,0.0005327885,0.0007086995,0.0004417583,0.0001172824,0.002934072],"category_scores_gemma":[0.00501608,0.0001506567,0.0003379234,0.00377594,0.0008553157,0.00103453,0.000310713,0.0001870912,0.0001013469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001805872,"about_ca_system_score_gemma":0.0007021707,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002675673,"about_ca_topic_score_gemma":0.02335101,"domain_scores_codex":[0.9970844,0.0004102405,0.0004898971,0.0006933821,0.0007649595,0.0005571709],"domain_scores_gemma":[0.9975865,0.001184175,0.0000848718,0.0004464375,0.0004164947,0.0002814854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008163854,0.0005164433,0.9643229,0.00004060113,0.0001954351,0.00001441967,0.001546527,0.00001654383,0.000265715,0.009693204,0.00007723938,0.02330279],"study_design_scores_gemma":[0.0004811122,0.00008939485,0.7778724,0.00003414739,0.000748471,0.00000379492,0.01833932,0.01584746,0.001367011,0.1810434,0.00315086,0.001022686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7295724,0.00003058607,0.0007129777,0.0009210618,0.0001072252,0.0001113974,0.000007518791,0.0002578931,0.268279],"genre_scores_gemma":[0.9930989,0.000002736324,0.001485327,0.0002763787,0.000148769,0.00001206416,0.00001828301,0.00001048134,0.004947103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2635265,"threshold_uncertainty_score":0.9979774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04211480257468035,"score_gpt":0.365715285434231,"score_spread":0.3236004828595507,"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."}}