{"id":"W2944050487","doi":"10.5267/j.ijiec.2019.4.002","title":"A modified sailfish optimizer to solve dynamic berth allocation problem in conventional container terminal","year":2019,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terminal (telecommunication); Container (type theory); Mathematical optimization; Computer science; Operations research; Engineering; Mathematics; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002473411,0.0001480142,0.0002274253,0.0005338282,0.00001340333,0.000084953,0.0002647667,0.0001006082,0.0001275044],"category_scores_gemma":[0.00009820708,0.0001573179,0.00009183268,0.0001827042,0.00001096112,0.0002032106,0.00003286799,0.0003654219,0.00001729357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966983,"about_ca_system_score_gemma":0.0001001654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002587065,"about_ca_topic_score_gemma":0.000009382892,"domain_scores_codex":[0.9986638,0.00001034958,0.0006727082,0.0001115714,0.0003691812,0.0001723829],"domain_scores_gemma":[0.9992467,0.0001302045,0.0001172291,0.00007345456,0.0003295545,0.000102836],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003853723,0.00004697048,0.0004856599,0.000008908076,0.0001080395,0.00004160845,0.00009759195,0.9923984,0.0003035159,0.002038003,0.0005563151,0.003876451],"study_design_scores_gemma":[0.002330108,0.00009673063,0.003190292,0.0003015075,0.00002111423,0.0001557415,0.00003956668,0.9902226,0.00006549364,0.0002777371,0.003064139,0.0002350071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3310171,0.00004825302,0.6619447,0.0009760075,0.004221884,0.0004351625,0.00005043584,0.00008243781,0.001224036],"genre_scores_gemma":[0.980554,0.000007033281,0.01890418,0.00004901479,0.000312441,0.00001000596,0.00005095249,0.00002567745,0.00008666936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6495369,"threshold_uncertainty_score":0.6415238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613858595115813,"score_gpt":0.2436492027699371,"score_spread":0.227510616818779,"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."}}