{"id":"W3144840300","doi":"10.1787/04525828-en","title":"High-occupancy Toll Lanes","year":2020,"lang":"en","type":"paratext","venue":"Discussion papers","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Toll; Occupancy; Context (archaeology); Transport engineering; Metering mode; Computer science; Traffic congestion; Geography; Engineering; Civil 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000117373,0.0002105586,0.0002940847,0.00007803473,0.000503666,0.00009744631,0.0002574604,0.000357052,0.01509381],"category_scores_gemma":[0.0000641516,0.0001318366,0.0001242843,0.0002740416,0.0001015049,0.0001047298,0.00001114466,0.0002682897,0.005132175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004826509,"about_ca_system_score_gemma":0.0002884827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006474298,"about_ca_topic_score_gemma":0.0003424873,"domain_scores_codex":[0.9984482,0.0001546024,0.0002636906,0.0003733722,0.0004874776,0.0002726425],"domain_scores_gemma":[0.9993739,0.00004706415,0.0001752985,0.0001446736,0.00004654377,0.0002125312],"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":[0.00004234094,0.00003197776,0.0003719524,0.00006890642,0.00003731287,0.00001421841,0.01371279,0.001633204,0.0000385167,0.002626305,0.9749448,0.006477675],"study_design_scores_gemma":[0.0001821688,0.00001744991,0.0006854355,0.000117968,0.00003349286,9.986268e-8,0.003184449,0.000006350095,0.00001100531,0.00003318591,0.9954636,0.0002647928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002634582,0.0004401339,0.0002632095,0.01672406,0.005935284,0.0003904926,0.0003739067,0.0002596244,0.9753498],"genre_scores_gemma":[0.07130047,0.001824214,0.0006937368,0.001078147,0.001323616,0.0000374617,0.004868645,0.00005390846,0.9188198],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07103701,"threshold_uncertainty_score":0.9956424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01586391875677931,"score_gpt":0.2902604794946327,"score_spread":0.2743965607378533,"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."}}