{"id":"W4403821286","doi":"10.1155/2024/5793435","title":"Reconstruction of the Motion of Traffic Accident Vehicle in the Vehicle‐Mounted Video Based on Direct Linear Transform","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Vehicle accident; Computer science; Motion (physics); Traffic accident; Computer vision; Artificial intelligence; Engineering; Transport engineering; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002153386,0.0007238087,0.0003872959,0.001071776,0.0001849081,0.0004663753,0.000461982,0.0003954626,0.001027719],"category_scores_gemma":[0.0008783737,0.0003178701,0.0005320178,0.0009625,0.0002540266,0.0007032798,0.0004844666,0.0005548217,0.0004156342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002456979,"about_ca_system_score_gemma":0.0005652576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003434495,"about_ca_topic_score_gemma":0.003097993,"domain_scores_codex":[0.99975,0.00002664097,0.00001086993,0.00006467674,0.0001189743,0.00002897141],"domain_scores_gemma":[0.9997711,0.00003543622,0.00003434511,0.00003287218,0.0001115829,0.00001477971],"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":[0.000436573,0.0000969666,0.009993624,0.0004973615,0.0001287115,0.0007985914,0.0004533087,0.1824779,0.2106441,0.005689309,0.003414991,0.5853686],"study_design_scores_gemma":[0.0000277799,0.0001322588,0.01037917,0.00003431832,0.0000499674,0.0005295509,0.000213122,0.9322197,0.05159165,0.00117983,0.003582479,0.00006014971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1172496,0.0002785873,0.8789095,0.00009433242,0.0000839961,0.00006230344,0.0004174779,0.000590011,0.0023142],"genre_scores_gemma":[0.6869476,0.0008478152,0.3067297,0.00006882485,0.0000726638,0.0001018598,0.001438062,0.0001297012,0.00366386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003434495,"threshold_uncertainty_score":0.006829023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005011396918685546,"score_gpt":0.2213168038224516,"score_spread":0.216305406903766,"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."}}