{"id":"W3195489957","doi":"10.1155/2021/4592124","title":"Traffic Flow Parameters Collection under Variable Illumination Based on Data Fusion","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; National Key Research and Development Program of China","keywords":"Robustness (evolution); Computer science; Sensor fusion; Computer vision; Data collection; Radar; Artificial intelligence; Adaptability; Detector; Clutter; Remote sensing; Mathematics; Geography","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":[0.0004759049,0.0007623004,0.0006492717,0.001592461,0.0002954984,0.0005821028,0.0006288716,0.000446121,0.0005297614],"category_scores_gemma":[0.001188959,0.0002180825,0.000533819,0.001031805,0.0002991753,0.001203937,0.0007411018,0.0006735894,0.0003863445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004052795,"about_ca_system_score_gemma":0.0004726485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002750864,"about_ca_topic_score_gemma":0.003030624,"domain_scores_codex":[0.9995087,0.00005642211,0.00002019562,0.0001739484,0.0001495601,0.00009122466],"domain_scores_gemma":[0.9996245,0.00004300389,0.00004338137,0.00007518365,0.000187275,0.00002663443],"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":[0.0004655693,0.0004311621,0.01836433,0.0002073961,0.0001760106,0.0002055389,0.0002273627,0.1002266,0.1231261,0.001428423,0.006085515,0.749056],"study_design_scores_gemma":[0.00002656443,0.0001300263,0.02317564,0.00002114708,0.00009112268,0.0001922386,0.0001543552,0.8991005,0.07173815,0.002133559,0.003182803,0.00005391581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4414027,0.0003776879,0.546881,0.0002308615,0.0001859812,0.0001531825,0.001330565,0.003968638,0.005469357],"genre_scores_gemma":[0.862568,0.0002700628,0.1326245,0.00009350735,0.00007943467,0.00009392078,0.002906979,0.0001112746,0.001252268],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002750864,"threshold_uncertainty_score":0.005469739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03093778077607018,"score_gpt":0.293678065530852,"score_spread":0.2627402847547818,"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."}}