{"id":"W4407027289","doi":"10.2139/ssrn.5119349","title":"Speed Limit Estimation Using Graph Neural Networks","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Limit (mathematics); Artificial neural network; Graph; Estimation; Artificial intelligence; Mathematics; Theoretical computer science; 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":[0.0004655684,0.0007307032,0.000829505,0.001590681,0.0003244822,0.0009450484,0.0009720011,0.001099672,0.001767457],"category_scores_gemma":[0.003830027,0.0005062671,0.0004061656,0.001410222,0.0004086208,0.001468735,0.0005512541,0.001012576,0.0004368157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006207888,"about_ca_system_score_gemma":0.0005032622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132707,"about_ca_topic_score_gemma":0.008144014,"domain_scores_codex":[0.9997867,0.00005702862,0.00001044286,0.00006660623,0.00004709165,0.00003209289],"domain_scores_gemma":[0.9983926,0.001075743,0.000149701,0.00009302305,0.0002419247,0.00004689422],"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":[0.00008672219,0.00004710091,0.001364469,0.0000408148,0.00003929938,0.00003340987,0.00001819922,0.9224393,0.001094193,0.00402128,0.001218454,0.06959679],"study_design_scores_gemma":[7.912883e-7,0.000002085702,0.00006517364,0.000001390437,0.000001418464,0.000001850019,8.102239e-7,0.9983506,0.00009003875,0.001449006,0.00003584808,9.759233e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0576785,0.0004664875,0.9382449,0.0002309085,0.00008257396,0.0000288258,0.0001401464,0.001008322,0.002119422],"genre_scores_gemma":[0.916427,0.0002949602,0.0793558,0.00007834189,0.00006728923,0.00004911219,0.0002877057,0.0001047711,0.003334938],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01132707,"threshold_uncertainty_score":0.02252233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050879082436989,"score_gpt":0.2387255967804995,"score_spread":0.2282168059561296,"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."}}