{"id":"W635577806","doi":"","title":"Terminal Appointment System Study","year":2006,"lang":"en","type":"article","venue":"","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Reservation; Port (circuit theory); Terminal (telecommunication); Reservation system; Truck; Transport engineering; Automation; Engineering; Environmental economics; Business; Operations management; Telecommunications; Computer science; Automotive engineering; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001521034,0.0002936325,0.0003247803,0.001688154,0.002157551,0.001571628,0.001126577,0.0006828028,0.04783005],"category_scores_gemma":[0.005050146,0.0001786411,0.0007943961,0.00249424,0.000484262,0.001111318,0.001320409,0.00105321,0.005464499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003855858,"about_ca_system_score_gemma":0.00785227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05613183,"about_ca_topic_score_gemma":0.07136655,"domain_scores_codex":[0.9984639,0.0003428759,0.00009746611,0.0001949397,0.0005272687,0.0003735666],"domain_scores_gemma":[0.9966119,0.0009427824,0.0003319632,0.0002433719,0.001263577,0.0006063535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003047308,0.005416215,0.2914295,0.002417532,0.0001966276,0.008634416,0.01212934,0.01038735,0.007687646,0.09798671,0.1246138,0.4360535],"study_design_scores_gemma":[0.0003816736,0.004387357,0.2868148,0.0004297694,0.0002556828,0.003949817,0.01728756,0.007209057,0.005820191,0.00451495,0.668811,0.0001381605],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5846927,0.00154694,0.00958775,0.001699991,0.0005523226,0.002238856,0.00895867,0.0002590416,0.3904639],"genre_scores_gemma":[0.8384359,0.002147101,0.004969565,0.00113755,0.0001886936,0.0006432229,0.007572379,0.00008874923,0.1448167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05613183,"threshold_uncertainty_score":0.1600074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005413396150960132,"score_gpt":0.1779393095619279,"score_spread":0.1725259134109678,"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."}}