{"id":"W4251750770","doi":"10.1177/0361198105193700110","title":"Assessing Multifunction Interfaces in Vehicles","year":2005,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Carleton University; Transport Canada","funders":"","keywords":"Usability; Heuristic evaluation; Cognitive walkthrough; Usability goals; Usability inspection; Computer science; Heuristic; Web usability; Usability engineering; Human–computer interaction; User interface; Simulation; Engineering; Artificial intelligence; Operating system","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":[0.005465852,0.0005360868,0.0003200483,0.001483746,0.0003844912,0.001224552,0.0004858317,0.0006602706,0.002046733],"category_scores_gemma":[0.03149559,0.0002323979,0.0003452333,0.0004908972,0.0005517837,0.001253246,0.0008568052,0.0003411771,0.0002808805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006667385,"about_ca_system_score_gemma":0.0006234976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001501689,"about_ca_topic_score_gemma":0.001633755,"domain_scores_codex":[0.9958401,0.001492865,0.0002941319,0.0002986761,0.001829547,0.0002446986],"domain_scores_gemma":[0.9745429,0.01416999,0.004220239,0.0009466166,0.005465277,0.000654862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002558002,0.001971164,0.4449279,0.00151201,0.0002615924,0.0004555943,0.01324495,0.01037501,0.1710618,0.00160072,0.001083765,0.3509475],"study_design_scores_gemma":[0.0001014298,0.01315311,0.8954388,0.0002049828,0.0002202906,0.001005749,0.00813502,0.0241703,0.05035758,0.003496127,0.003546326,0.0001702482],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898785,0.0001411743,0.008096734,0.00003351423,0.000007985815,0.00007090336,0.00001737691,0.00005999714,0.001693738],"genre_scores_gemma":[0.9919277,0.00008420234,0.007510634,0.00002040997,0.000005839519,0.00002597477,0.00003374217,0.000009280246,0.0003821542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005465852,"threshold_uncertainty_score":0.02890652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1732445604454897,"score_gpt":0.4961412956905519,"score_spread":0.3228967352450622,"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."}}