{"id":"W4210476644","doi":"10.1155/2022/3927268","title":"Exact Algorithms for Practical Instances of the Railcar Loading Problem at Marine Container Terminals","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan","keywords":"DOCK; Train; Container (type theory); Traverse; Terminal (telecommunication); Computer science; Stack (abstract data type); Freight trains; Containerization; Algorithm; Operations research; Engineering; Marine engineering; Computer network; Mechanical engineering; Geology","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":[0.0002436572,0.00008180796,0.0001912097,0.00004770416,0.0000822187,0.000005647762,0.00008152484,0.00002158134,0.0001211904],"category_scores_gemma":[0.00002589303,0.00006213835,0.0001101871,0.00009580961,0.00002381154,0.0002075186,0.000004910651,0.0001718815,7.305596e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007968501,"about_ca_system_score_gemma":0.00004164328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003402203,"about_ca_topic_score_gemma":0.00004347357,"domain_scores_codex":[0.9990763,0.00001557232,0.0004946378,0.00006127686,0.0002401158,0.0001120745],"domain_scores_gemma":[0.9993604,0.0001029524,0.0003235501,0.00006878233,0.0001112113,0.00003311304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006046115,0.0001401605,0.008405399,0.0004935527,0.000164509,0.00008091419,0.0017217,0.9296021,0.01822417,0.003459926,0.0007190056,0.03638389],"study_design_scores_gemma":[0.01605452,0.003558784,0.4107712,0.0006322926,0.001526998,0.0008568643,0.007106177,0.02336655,0.07161487,0.03073989,0.4321774,0.001594414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.906054,0.0005908385,0.08793142,0.0009195422,0.001761786,0.0009245374,0.0002359199,0.00004689869,0.001535065],"genre_scores_gemma":[0.9730492,0.00007938527,0.02658524,0.00002595985,0.00006865696,0.00001839727,0.00001987402,0.00001720297,0.0001360694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9062356,"threshold_uncertainty_score":0.2533928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01621332409001933,"score_gpt":0.2658899049965205,"score_spread":0.2496765809065012,"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."}}