{"id":"W2115549353","doi":"10.1016/j.aap.2011.07.006","title":"How fleeting emotions affect hazard perception and steering while driving: The impact of image arousal and valence","year":2011,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of Guelph","funders":"Ontario Innovation Trust","keywords":"Arousal; Valence (chemistry); Driving simulator; Steering wheel; Affect (linguistics); Perception; Psychology; Negative emotion; Simulation; Computer science; Computer vision; Automotive engineering; Social psychology; Engineering; Communication; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000581949,0.0001275675,0.0002142237,0.0002909859,0.000186424,0.0001079945,0.0001010839,0.00006073346,0.002578498],"category_scores_gemma":[0.00005876515,0.00009826744,0.000299336,0.0003321553,0.00005930927,0.0004854336,0.00005295219,0.000125042,0.00001919339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004393357,"about_ca_system_score_gemma":0.0000075585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003181766,"about_ca_topic_score_gemma":0.0008781128,"domain_scores_codex":[0.9988304,0.0003304032,0.0002969393,0.0002559738,0.0001405417,0.0001457933],"domain_scores_gemma":[0.9991943,0.00008178328,0.0003117023,0.000268866,0.00009212819,0.00005120823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003447794,0.0001267813,0.9714236,0.000005100792,0.001236419,0.000001500747,0.008289734,0.00004562604,0.005490986,0.0002948674,0.0003102115,0.01274072],"study_design_scores_gemma":[0.00019869,0.00009279196,0.9926767,0.00002944416,0.0006245921,0.00001175819,0.002761978,0.003234302,0.00008425568,0.0001819547,0.00001036941,0.00009313667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715977,0.00005024991,0.02637456,0.00008825386,0.0000877417,0.0001811026,6.933016e-7,0.00004636283,0.001573373],"genre_scores_gemma":[0.9982119,0.00004823666,0.000384711,0.000005449251,0.0000453385,0.00002233513,0.00002235129,0.000009823922,0.001249842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02661425,"threshold_uncertainty_score":0.9983333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04043657718930734,"score_gpt":0.3618701203769916,"score_spread":0.3214335431876843,"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."}}