{"id":"W2398959625","doi":"10.1080/03088839.2016.1237783","title":"Internalization of port congestion: strategic effect behind shipping line delays and implications for terminal charges and investment","year":2016,"lang":"en","type":"article","venue":"Maritime Policy & Management","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Manitoba","funders":"Research Grants Council, University Grants Committee","keywords":"Terminal (telecommunication); Profit (economics); Stackelberg competition; Microeconomics; Business; Economics; Computer science; Industrial organization; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00184856,0.0008453248,0.0009173082,0.0008183702,0.001066047,0.003766886,0.001728118,0.002530271,0.01376163],"category_scores_gemma":[0.007573434,0.000883255,0.001406601,0.0008605951,0.00398482,0.005572358,0.002083241,0.003396708,0.0004663217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00749144,"about_ca_system_score_gemma":0.002958714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01179841,"about_ca_topic_score_gemma":0.009300654,"domain_scores_codex":[0.9985549,0.0003808044,0.00004461862,0.0002046837,0.0002107045,0.0006042455],"domain_scores_gemma":[0.9951025,0.002500499,0.001256925,0.0002541546,0.0003883245,0.000497479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001260242,0.0001417055,0.006496793,0.0001354605,0.00006453446,0.0006619445,0.0003249864,0.3046036,0.002121591,0.6774561,0.001146848,0.00672035],"study_design_scores_gemma":[0.0001231854,0.0003562081,0.01259247,0.0001224308,0.0001895649,0.0004805098,0.001537821,0.473822,0.0018748,0.5041044,0.004623213,0.0001734339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6175236,0.0009210559,0.2414505,0.005512652,0.0001416922,0.0002467366,0.0004414828,0.0002052889,0.1335569],"genre_scores_gemma":[0.9937149,0.0002347424,0.001814031,0.00007681652,0.00002182751,0.00002647677,0.00002014058,0.00001150895,0.004079631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01376163,"threshold_uncertainty_score":0.05435443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214731646923747,"score_gpt":0.2693439331705438,"score_spread":0.2471966167013063,"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."}}