{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001665408,0.0009802795,0.002759937,0.001147452,0.0005370121,0.00003150964,0.004640549,0.001702588,0.00180224],"category_scores_gemma":[0.0001403778,0.001360615,0.0006156465,0.001388523,0.0005709339,0.0004533507,0.001854034,0.001898034,0.0001559519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008411128,"about_ca_system_score_gemma":0.001249863,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004320961,"about_ca_topic_score_gemma":0.05215424,"domain_scores_codex":[0.9947295,0.0002622402,0.001232704,0.002069086,0.000843538,0.0008629423],"domain_scores_gemma":[0.9922189,0.0001645125,0.0006771499,0.005825037,0.0008226239,0.0002917927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001038518,0.01578201,0.3775563,0.02325159,0.01285406,0.003047802,0.01923896,0.0001389028,0.0002309973,0.001244465,0.2405995,0.3050168],"study_design_scores_gemma":[0.004815674,0.000624693,0.3067114,0.001774631,0.00341014,0.00003212683,0.009526569,0.0007831702,0.000009767208,0.00007437323,0.6706575,0.001579969],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5859215,0.01146062,0.00898694,0.0004222542,0.01846445,0.009848375,0.008591509,0.001872385,0.354432],"genre_scores_gemma":[0.9724189,0.001731565,0.0004527941,0.00000272529,0.0002890633,0.000001766518,0.001196169,0.00008525423,0.02382176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.430058,"threshold_uncertainty_score":0.9995934,"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."}}