{"id":"W7111060652","doi":"10.13023/ktc.rr.2026.11","title":"IRP Commercial Trailer Data Feasibility Study","year":2025,"lang":"","type":"report","venue":"UKnowledge (University of Kentucky)","topic":"Transport Systems and Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trailer; License; Jurisdiction; Law enforcement; Enforcement; Identification (biology); Data collection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.1229445,0.0003982958,0.0004055719,0.004049239,0.003487008,0.006579042,0.004124288,0.001660567,0.02462764],"category_scores_gemma":[0.2150128,0.0007875646,0.0005973949,0.004230418,0.001795808,0.008788616,0.005044998,0.002600142,0.005223073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005594502,"about_ca_system_score_gemma":0.02179012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01364038,"about_ca_topic_score_gemma":0.01495974,"domain_scores_codex":[0.8983498,0.05131666,0.007420531,0.005981937,0.03252967,0.004401487],"domain_scores_gemma":[0.6552631,0.1445156,0.02069571,0.02973387,0.1358999,0.01389185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004027946,0.0155582,0.4183249,0.003148957,0.0001821591,0.004167253,0.03135069,0.003403075,0.007140111,0.03890611,0.0865081,0.3872826],"study_design_scores_gemma":[0.001783192,0.01527212,0.2930045,0.003152648,0.0002842578,0.004144982,0.1525275,0.02519795,0.01361198,0.007477399,0.4831303,0.0004131945],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7266945,0.0004078647,0.04212059,0.01664417,0.0005318486,0.03739321,0.01174979,0.001435815,0.1630222],"genre_scores_gemma":[0.8984055,0.000353375,0.06575897,0.002748212,0.0001789132,0.01656008,0.006097111,0.0002485189,0.009649192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1229445,"threshold_uncertainty_score":0.6502006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09915491119096491,"score_gpt":0.2815193085581336,"score_spread":0.1823643973671687,"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."}}