{"id":"W1974384698","doi":"10.1145/1358628.1358654","title":"A comparative evaluation of heuristic-based usability inspection methods","year":2008,"lang":"en","type":"article","venue":"","topic":"Usability and User Interface Design","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Usability; Heuristic evaluation; Heuristics; Reliability (semiconductor); Computer science; Heuristic; Set (abstract data type); Usability inspection; Usability goals; Outcome (game theory); Cognitive walkthrough; Reliability engineering; Artificial intelligence; Human–computer interaction; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.05251221,0.0009762834,0.001093065,0.006012344,0.0006343107,0.002187196,0.001696741,0.001062935,0.001050312],"category_scores_gemma":[0.1757955,0.0003916049,0.000685156,0.002572644,0.0009739997,0.002223124,0.002021954,0.0007573302,0.0002548885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001783065,"about_ca_system_score_gemma":0.001600034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002105887,"about_ca_topic_score_gemma":0.002666986,"domain_scores_codex":[0.9117541,0.06005362,0.005759108,0.002366441,0.01913488,0.000931876],"domain_scores_gemma":[0.6961073,0.2491896,0.009554538,0.01306715,0.0298171,0.002264287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007877689,0.003271741,0.03738449,0.004298577,0.0009483906,0.0001731282,0.007220189,0.01689573,0.007277508,0.005259529,0.001925554,0.9074674],"study_design_scores_gemma":[0.004310925,0.05322368,0.3362209,0.003349138,0.002067758,0.002220817,0.0145229,0.4999045,0.04105767,0.01632195,0.02571337,0.001086348],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8259431,0.00462732,0.1470025,0.000385347,0.0001788979,0.002351765,0.0003117373,0.001301641,0.01789771],"genre_scores_gemma":[0.8354436,0.0009570521,0.160997,0.0001098107,0.00004195196,0.0008031516,0.000346623,0.00008593875,0.001214852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05251221,"threshold_uncertainty_score":0.2777144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.280983639764195,"score_gpt":0.4390775272608653,"score_spread":0.1580938874966702,"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."}}