{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001811581,0.001101126,0.0007379368,0.0067594,0.0007554985,0.001880427,0.001408892,0.0008980677,0.003002276],"category_scores_gemma":[0.0119337,0.0003688876,0.001299636,0.001739291,0.001075508,0.002250849,0.002020704,0.000723266,0.0009082919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001011685,"about_ca_system_score_gemma":0.001235241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01513076,"about_ca_topic_score_gemma":0.01295309,"domain_scores_codex":[0.9975507,0.0008555091,0.0001421871,0.0004537134,0.0008100308,0.0001878204],"domain_scores_gemma":[0.9937145,0.003016684,0.0006808625,0.000900584,0.001538238,0.0001491016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008325946,0.000682667,0.04281175,0.0005569895,0.0002625633,0.0008906419,0.001608968,0.1166343,0.03161938,0.02388087,0.009208466,0.7710108],"study_design_scores_gemma":[0.00002364017,0.00008412833,0.005260651,0.00004601669,0.00003821385,0.0001497674,0.0003459952,0.9609748,0.01097552,0.01980233,0.002272138,0.00002684514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1528337,0.0002207802,0.8223853,0.0002676288,0.00003218038,0.0003724324,0.001165358,0.01662797,0.006094592],"genre_scores_gemma":[0.741846,0.0001021582,0.254041,0.00008229972,0.00001781318,0.0001642948,0.002113368,0.0003458693,0.001287134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01513076,"threshold_uncertainty_score":0.03008538,"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."}}