{"id":"W4401414548","doi":"10.1109/icra57147.2024.10610614","title":"A Novel Benchmarking Paradigm and a Scale- and Motion-Aware Model for Egocentric Pedestrian Trajectory Prediction","year":2024,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Pedestrian; Trajectory; Benchmarking; Computer science; Scale (ratio); Motion (physics); Artificial intelligence; Computer vision; Geography; Transport engineering; Engineering; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008926351,0.0001045478,0.00009951613,0.0001150649,0.00008213338,0.00002993415,0.00003318594,0.0001459052,0.000007277542],"category_scores_gemma":[0.000003789704,0.0001012725,0.00002655721,0.00009765564,0.00003520135,0.0001306885,0.00001329938,0.0001273772,9.085177e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004446394,"about_ca_system_score_gemma":0.0000151981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000725389,"about_ca_topic_score_gemma":0.0000423194,"domain_scores_codex":[0.9994845,0.000002635652,0.0001296059,0.0001867629,0.00003830255,0.0001582353],"domain_scores_gemma":[0.9998227,0.00004689862,0.000006894779,0.00007358659,0.000006119192,0.00004374434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008834557,0.0001336872,0.014134,0.002861787,0.0004599339,0.00001774103,0.003346445,0.2708943,0.005570627,0.04049794,0.002526434,0.6594688],"study_design_scores_gemma":[0.0002816473,0.00002331901,0.002986666,0.0000278408,0.00003068921,0.00003564134,0.00003403428,0.9947575,0.0001034673,0.001367152,0.0002533224,0.00009875331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1647171,0.001133571,0.8324132,0.0001344638,0.0001213408,0.0002241761,0.00005189925,0.0009341713,0.0002701005],"genre_scores_gemma":[0.9960815,0.0002429868,0.003443192,0.00001217946,0.000054778,0.00004160729,0.00001330768,0.00001993902,0.00009055385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8313644,"threshold_uncertainty_score":0.4129774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205140769278121,"score_gpt":0.2066164653414644,"score_spread":0.1945650576486831,"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."}}