{"id":"W2950544301","doi":"10.3390/ijerph16122226","title":"Evaluating the Environmental Performance and Operational Efficiency of Container Ports: An Application to the Maritime Silk Road","year":2019,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Fundamental Research Funds for the Central Universities; Ministry of Education of the People's Republic of China; National Social Science Fund of China; Major Research Plan; National Natural Science Foundation of China","keywords":"Container (type theory); Data envelopment analysis; Port (circuit theory); Operational efficiency; Throughput; Operational effectiveness; Environmental pollution; Sustainable development; Transport engineering; Operations research; Business; Environmental economics; Computer science; Environmental science; Engineering; Environmental protection; Telecommunications; Economics","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":[0.002333593,0.001000872,0.0007148488,0.001477224,0.0004714264,0.001699632,0.0005944148,0.0008001758,0.000861484],"category_scores_gemma":[0.004462877,0.0002587455,0.001223695,0.002641069,0.0006874648,0.001801505,0.0009404626,0.0005713195,0.0001023224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002875764,"about_ca_system_score_gemma":0.001394928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04137247,"about_ca_topic_score_gemma":0.02086247,"domain_scores_codex":[0.9989096,0.000586522,0.0000512309,0.0001162751,0.0002055874,0.0001308826],"domain_scores_gemma":[0.9969316,0.00198041,0.0003933492,0.0001805895,0.0003932556,0.0001207725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003409009,0.0003226617,0.04881242,0.0001181597,0.0001892602,0.0004406965,0.0001678178,0.9280394,0.003850614,0.002526376,0.0003349119,0.01485687],"study_design_scores_gemma":[0.0000138426,0.0003004275,0.0220921,0.00001024566,0.00004988266,0.00004066883,0.0003639153,0.9742123,0.002031599,0.0005699543,0.0002881261,0.00002692148],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861671,0.0001434205,0.01204934,0.00009240727,0.000007979694,0.00003438702,0.0001449017,0.00004887009,0.001311461],"genre_scores_gemma":[0.9953447,0.00009751512,0.004116804,0.000005055668,0.000002880828,0.00001420683,0.00009611872,0.000009289862,0.0003135124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04137247,"threshold_uncertainty_score":0.08226335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04230184231132789,"score_gpt":0.351627264766144,"score_spread":0.3093254224548161,"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."}}