{"id":"W4391450589","doi":"10.1016/j.cja.2024.01.028","title":"Aerial refueling scheduling of multi-receiver and multi-tanker under spatial-temporal constraints for forest firefighting","year":2024,"lang":"en","type":"article","venue":"Chinese Journal of Aeronautics","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Key Research and Development Program of Jiangxi Province; National Natural Science Foundation of China","keywords":"Firefighting; Rendezvous; Scheduling (production processes); Fuel efficiency; Computer science; Engineering; Aerospace engineering; Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003833422,0.000739313,0.0007460528,0.0002751726,0.0004012643,0.0006968364,0.0006267635,0.0004944147,0.002235077],"category_scores_gemma":[0.0006003673,0.000275712,0.000624445,0.0003504449,0.0003000339,0.0005213008,0.0006488987,0.000552132,0.0001924512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006390181,"about_ca_system_score_gemma":0.001483841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01673182,"about_ca_topic_score_gemma":0.01345927,"domain_scores_codex":[0.9997969,0.0000396728,0.00000716352,0.00004628923,0.00004667515,0.00006330197],"domain_scores_gemma":[0.9997953,0.00007823644,0.0000377474,0.00001394554,0.00003977968,0.00003499898],"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":[0.00003725143,0.00001791811,0.0003454943,0.00004993814,0.000009614969,0.00006183438,0.00003161843,0.9870164,0.002406943,0.002130691,0.0004174026,0.007474971],"study_design_scores_gemma":[0.000004490921,0.00001429605,0.00008111378,0.000002233623,0.000003955777,0.000005667704,0.00001296073,0.9990288,0.0002614804,0.0003761803,0.0002066889,0.000002214762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1237873,0.0007753667,0.8639978,0.0002470372,0.00008171525,0.00007552879,0.0001335729,0.0002973936,0.01060429],"genre_scores_gemma":[0.9080115,0.0004253144,0.08741296,0.00006391144,0.00002688349,0.00009627019,0.0001486133,0.00006572994,0.003748946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01673182,"threshold_uncertainty_score":0.03326887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01504047619884703,"score_gpt":0.2528614304404456,"score_spread":0.2378209542415985,"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."}}