{"id":"W3126264610","doi":"10.1109/cavs51000.2020.9334636","title":"A Probabilistic Model for Visual Driver Gaze Approximation from Head Pose Estimation","year":2020,"lang":"en","type":"article","venue":"","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Gaze; Computer science; Probabilistic logic; Computer vision; Artificial intelligence; Advanced driver assistance systems; Process (computing); Gaussian process; Head (geology); Kriging; Situation awareness; Interval (graph theory); Eye tracking; Visual search; Visual angle; Human–computer interaction; Gaussian; Machine learning; Engineering; Mathematics","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":[0.001641141,0.0007197103,0.0008599599,0.001003865,0.0002991614,0.0007992579,0.001857773,0.001035938,0.001515952],"category_scores_gemma":[0.007370932,0.000682249,0.0009701877,0.0009007311,0.0006718026,0.001040287,0.0008560341,0.001368604,0.0005871508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007777976,"about_ca_system_score_gemma":0.0007844091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02114497,"about_ca_topic_score_gemma":0.01439453,"domain_scores_codex":[0.9993712,0.0001943923,0.00002958827,0.0001880862,0.000139724,0.00007696997],"domain_scores_gemma":[0.9978115,0.001472436,0.0002237502,0.0001336276,0.0003139697,0.00004470087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002569129,0.00007536236,0.004832579,0.00009691717,0.0001111237,0.0001539182,0.0002294595,0.9128872,0.004760725,0.0165756,0.001745294,0.05827483],"study_design_scores_gemma":[0.000005808592,0.00001290006,0.0006638792,0.000004593191,0.000008574168,0.00002324523,0.000005408768,0.9961385,0.0001996923,0.002773616,0.0001552977,0.00000843768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0439603,0.0004018069,0.9537597,0.0002789127,0.00003464132,0.00003733793,0.0002601173,0.0004697739,0.0007974805],"genre_scores_gemma":[0.9180656,0.0007879955,0.07574659,0.0001447952,0.0001102158,0.0001847898,0.0007414325,0.0001333384,0.00408529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02114497,"threshold_uncertainty_score":0.04204375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03553313601755526,"score_gpt":0.2803356295545801,"score_spread":0.2448024935370249,"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."}}