{"id":"W6963725807","doi":"10.21227/t90a-8h78","title":"Transportation Networks used in experiments for DRL-Router (Sioux Falls, Anaheim, Winnipeg, Barcelona)","year":2021,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intersection (aeronautics); Identification (biology); Work (physics); Feature (linguistics); 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"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0009954142,0.00128751,0.001645454,0.0007000975,0.0001711655,0.0002528345,0.001676592,0.001216296,0.0007201782],"category_scores_gemma":[0.00006461189,0.001455558,0.0004350492,0.001010373,0.0001599464,0.0009066052,0.00008628594,0.001143349,0.0007460272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000487223,"about_ca_system_score_gemma":0.0006401655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001780159,"about_ca_topic_score_gemma":0.01728491,"domain_scores_codex":[0.9929304,0.0002062075,0.001864681,0.002269145,0.001289256,0.001440307],"domain_scores_gemma":[0.9950653,0.0001729938,0.0009032929,0.003197659,0.000249082,0.0004116117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002964767,0.0006461319,0.0008699949,0.0002581116,0.0003118477,0.0008762148,0.000132315,0.0006479034,0.0005512999,0.000001924843,0.9952779,0.0001298801],"study_design_scores_gemma":[0.003049108,0.0001064559,0.002432114,0.000502722,0.000411954,0.00001349988,0.0001481337,0.0003369545,0.0005737016,0.000006750962,0.9909356,0.001483069],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00325469,0.0006526869,0.0008230039,0.00002339113,0.002629437,0.002347053,0.9901048,0.0001515021,0.00001341704],"genre_scores_gemma":[0.0009139659,0.0001859276,0.0007174271,0.0004960446,0.001038187,0.001193234,0.9948316,0.0003946777,0.0002289837],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01550475,"threshold_uncertainty_score":0.9999877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04664469074802705,"score_gpt":0.3254865799051906,"score_spread":0.2788418891571636,"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."}}