{"id":"W4408146128","doi":"10.1109/icmla61862.2024.00146","title":"Pedestrian Detection: An Explainable Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Pedestrian; Computer science; Pedestrian detection; Computer vision; Artificial intelligence; Transport engineering; Engineering","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":[0.0008861498,0.001253687,0.0007315909,0.001466414,0.0004507575,0.001008446,0.001765541,0.001562544,0.003292484],"category_scores_gemma":[0.002895837,0.000713594,0.001298871,0.00062221,0.0007479806,0.001681925,0.001745361,0.001491042,0.001040131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009490222,"about_ca_system_score_gemma":0.0008584796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008332732,"about_ca_topic_score_gemma":0.01090667,"domain_scores_codex":[0.9994264,0.0001355599,0.00001846871,0.0002407061,0.0001198122,0.00005910988],"domain_scores_gemma":[0.9991701,0.000322429,0.00009354206,0.0001913307,0.000178851,0.0000437693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006477098,0.000189504,0.0112362,0.0002350185,0.0003042813,0.0006157417,0.0004190105,0.435241,0.01912135,0.02912174,0.01515306,0.4877154],"study_design_scores_gemma":[0.00001148597,0.00004092536,0.0008807064,0.00001684728,0.00002767429,0.0001199815,0.00001897899,0.9806209,0.002430834,0.01344573,0.00237136,0.00001459641],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03693912,0.0004450826,0.9557981,0.0008461708,0.00008592592,0.00006202673,0.0005131387,0.003365582,0.00194479],"genre_scores_gemma":[0.7059403,0.0006134814,0.2831524,0.0006091362,0.000242683,0.000105096,0.001869567,0.0003945116,0.007072893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008332732,"threshold_uncertainty_score":0.01656848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007842455387717918,"score_gpt":0.1972307937826798,"score_spread":0.1893883383949619,"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."}}