{"id":"W4410286842","doi":"10.1080/03155986.2025.2502296","title":"Data envelopment analysis on measuring greenhouse gas emissions of liner shipping companies for reducing marine pollution","year":2025,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Data envelopment analysis; Environmental science; Pollution; Environmental economics; Business; Air pollution; Environmental engineering; Natural resource economics; Economics; Mathematics; Statistics; Oceanography","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":[0.002209997,0.00008750044,0.0001692017,0.0004415888,0.0005784912,0.0001427998,0.000258391,0.00005756314,0.0002113006],"category_scores_gemma":[0.0002724406,0.00006997162,0.00003576059,0.000801368,0.00009109428,0.0008099619,0.000258059,0.0001208633,0.00001207072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001126095,"about_ca_system_score_gemma":0.0001116735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001561194,"about_ca_topic_score_gemma":0.0001008672,"domain_scores_codex":[0.9983254,0.00004014745,0.0005984236,0.0001655323,0.0006687253,0.000201739],"domain_scores_gemma":[0.9992234,0.0001614842,0.00008036423,0.0003077039,0.0001441377,0.00008290721],"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":[0.0003822404,0.0002501563,0.0446318,0.0007277725,0.0003813191,7.05981e-7,0.002833526,0.7972733,0.001861274,0.03711225,0.01392063,0.100625],"study_design_scores_gemma":[0.0006322068,0.00009322369,0.06597281,0.0002445219,0.00004672664,0.000001743862,0.001234575,0.7777919,0.00041575,0.00005190897,0.1533394,0.0001752527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8102544,0.0001236705,0.0700742,0.002366964,0.0002873455,0.002872396,0.0008573765,0.00007780724,0.1130859],"genre_scores_gemma":[0.9963939,0.00005152557,0.001313799,0.00005365613,0.00001723792,0.00005914844,0.0005661663,0.000002787767,0.001541748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1861396,"threshold_uncertainty_score":0.4449345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09142824872139767,"score_gpt":0.3462925093416618,"score_spread":0.2548642606202642,"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."}}