{"id":"W205873924","doi":"","title":"MEASURING ECONOMIC BENEFITS OF INTERMODAL TRANSPORTATION","year":2000,"lang":"en","type":"article","venue":"Digital Commons - DU (University of Denver)","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Macro; Spillover effect; Productivity; Activity-based costing; Order (exchange); Economics; Transport engineering; Risk analysis (engineering); Environmental economics; Industrial organization; Business; Engineering; Computer science; Microeconomics; Economic growth; Finance","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":[],"consensus_categories":[],"category_scores_codex":[0.00007618909,0.00009865833,0.0003187831,0.0001539278,0.00006501804,0.00001931392,0.0002883559,0.00006860707,0.0006414182],"category_scores_gemma":[0.000005297689,0.0001535322,0.0001773733,0.00006762093,0.0001201174,0.000743605,0.00002129964,0.00006813652,0.0004325178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006620845,"about_ca_system_score_gemma":0.00001027757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000722707,"about_ca_topic_score_gemma":0.000444615,"domain_scores_codex":[0.9993405,0.000004099476,0.0002899977,0.0001981458,0.00001891626,0.0001483184],"domain_scores_gemma":[0.9995043,0.00002737098,0.000200818,0.0001911703,0.00001009603,0.00006624932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002959619,0.0003070404,0.632479,0.00009860044,0.0002720755,0.000007487836,0.004152794,0.002297138,0.000008575221,0.3348536,0.0014661,0.0237616],"study_design_scores_gemma":[0.00168731,0.0001795071,0.9515981,0.00005633834,0.00002433694,0.000005829437,0.0005352714,0.003152933,0.0001439479,0.03221186,0.009935059,0.0004694826],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8670709,0.00007494067,0.00008846373,0.0001669985,0.00004776839,0.00005573883,0.0009588219,0.00001640791,0.13152],"genre_scores_gemma":[0.9995278,0.00003014499,0.000046321,0.00001391918,0.00002235855,1.496379e-7,0.00005192009,0.000009826799,0.0002975822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3191191,"threshold_uncertainty_score":0.7023079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02981912374225406,"score_gpt":0.1604942661405579,"score_spread":0.1306751423983039,"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."}}