{"id":"W2273564813","doi":"","title":"Reverse engineering of content to find usability problems: a healthcare case study","year":2012,"lang":"en","type":"article","venue":"Journal of Usability Studies archive","topic":"Usability and User Interface Design","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"","keywords":"Usability; Usability engineering; Artifact (error); Computer science; System usability scale; Pluralistic walkthrough; Usability inspection; Reverse engineering; Task (project management); Human–computer interaction; Usability lab; Web usability; Heuristic evaluation; Cognitive walkthrough; Usability goals; Software engineering; Engineering; Artificial intelligence; Systems engineering; 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":[0.01178772,0.0008054962,0.0008056083,0.001851508,0.003553027,0.002292877,0.00184979,0.004799711,0.001336699],"category_scores_gemma":[0.0306565,0.0005540148,0.0009698873,0.001453579,0.002547077,0.002810005,0.002384809,0.001673118,0.0006292082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001659886,"about_ca_system_score_gemma":0.001992214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002648829,"about_ca_topic_score_gemma":0.00443487,"domain_scores_codex":[0.9854398,0.01000049,0.0008885317,0.0006507528,0.002289554,0.000730803],"domain_scores_gemma":[0.9520714,0.037641,0.00213577,0.003297102,0.003658983,0.001195727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001912518,0.01184627,0.08114211,0.004980889,0.0002950473,0.157297,0.2913305,0.006792006,0.03073471,0.01356461,0.01446449,0.3856398],"study_design_scores_gemma":[0.001211027,0.01529216,0.0580989,0.004391682,0.0007202172,0.2915401,0.2635145,0.05338707,0.1297777,0.01603534,0.165207,0.000824329],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9265653,0.001651768,0.05787843,0.004414891,0.0001129989,0.001732342,0.0001563451,0.0002224304,0.007265441],"genre_scores_gemma":[0.9237832,0.001357807,0.06863798,0.001165448,0.00006296584,0.0005011688,0.0001246829,0.0001096499,0.00425689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01178772,"threshold_uncertainty_score":0.0623402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1618908591463823,"score_gpt":0.3430565840768054,"score_spread":0.1811657249304231,"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."}}