{"id":"W2898655989","doi":"10.1145/3236024.3264592","title":"Vista: web test repair using computer vision","year":2018,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Test (biology); World Wide Web; Human–computer interaction; Geology","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":[0.001340786,0.001358575,0.0008623062,0.005461779,0.0005164248,0.001860436,0.002391149,0.001354865,0.004415715],"category_scores_gemma":[0.008364926,0.0007534045,0.001145505,0.001742542,0.0005794877,0.002096261,0.001748329,0.001501322,0.00440423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008951059,"about_ca_system_score_gemma":0.001114778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006293408,"about_ca_topic_score_gemma":0.0086566,"domain_scores_codex":[0.9983733,0.0002023097,0.000123392,0.0004159011,0.0007563378,0.0001287456],"domain_scores_gemma":[0.9961932,0.001004293,0.0006270666,0.001137304,0.0008253324,0.0002128248],"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":[0.0004116099,0.0004167026,0.01055802,0.0004142732,0.0002452401,0.0003546809,0.0002017642,0.0207801,0.02490576,0.004002497,0.1121874,0.8255219],"study_design_scores_gemma":[0.0001086973,0.0002521133,0.008544529,0.00009002273,0.00005471126,0.0007432913,0.0001350698,0.8947471,0.05080055,0.009884621,0.03455792,0.00008141047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03282522,0.0008819504,0.646261,0.0003802341,0.000189552,0.0006021864,0.004562869,0.3081098,0.006187202],"genre_scores_gemma":[0.262963,0.0003852882,0.7066371,0.0003465824,0.00009355332,0.0005684053,0.01556053,0.007666355,0.005779161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006293408,"threshold_uncertainty_score":0.01477206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191260796483109,"score_gpt":0.2794728682986082,"score_spread":0.2603467886502973,"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."}}