{"id":"W4408966500","doi":"10.1016/j.enconman.2025.119742","title":"Reducing carbon footprint in ports through electrification and flexible energy management of ships","year":2025,"lang":"en","type":"article","venue":"Energy Conversion and Management","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"European Commission","keywords":"Electrification; Carbon footprint; Footprint; Environmental science; Energy management; Energy (signal processing); Carbon fibers; Engineering; Automotive engineering; Environmental economics; Greenhouse gas; Computer science; Electricity; Electrical engineering; Economics; Oceanography; Geology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000163156,0.0001024962,0.0001152762,0.00009402923,0.00006467159,0.000009475028,0.00009329525,0.0000382711,0.0001182437],"category_scores_gemma":[6.167768e-7,0.00009949345,0.00001989964,0.0003149699,0.0000647827,0.00003520488,0.0001330069,0.00003530595,4.560767e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005843744,"about_ca_system_score_gemma":0.000003220423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00250723,"about_ca_topic_score_gemma":0.00005119267,"domain_scores_codex":[0.9991204,0.00002182037,0.0002111612,0.0003385319,0.00014217,0.0001659092],"domain_scores_gemma":[0.9997109,0.00000811103,0.00004783478,0.0001900548,0.000003289292,0.00003982623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001071629,0.0003478027,0.01014452,0.0004263446,0.00006922152,0.00006265118,0.0003347828,0.002141894,0.003007494,0.3901318,0.0008328261,0.5923935],"study_design_scores_gemma":[0.003523769,0.0001955348,0.1809026,0.0009056544,0.0002174432,0.000004994386,0.002129166,0.0164484,0.06032819,0.01011704,0.7243904,0.0008368124],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4254911,0.001027272,0.009701291,0.0008685928,0.0001865811,0.0002817198,6.756566e-7,0.00005851214,0.5623843],"genre_scores_gemma":[0.9833656,0.005458662,0.0009074028,0.0001117791,0.000002267626,0.00001365533,0.000005363706,0.000004477996,0.01013081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7235576,"threshold_uncertainty_score":0.4057225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006003618082878134,"score_gpt":0.2054789352879593,"score_spread":0.1994753172050812,"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."}}