{"id":"W4415140567","doi":"10.1016/j.ins.2025.122763","title":"Hesitant fuzzy linguistic term set based preference representation for composite decision makers in the graph model for conflict resolution","year":2025,"lang":"en","type":"article","venue":"Information Sciences","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for International Governance Innovation; University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Preference; Fuzzy logic; Term (time); Semantics (computer science); Group decision-making; Conflict resolution; Fuzzy set; Representation (politics); Set (abstract data type)","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":[0.002414657,0.000676234,0.0008689997,0.001299211,0.0005764178,0.002438551,0.001458099,0.001066608,0.004069378],"category_scores_gemma":[0.004871089,0.0002908039,0.0009869528,0.001550979,0.0008662513,0.003314386,0.001021812,0.00146155,0.0003743701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001419804,"about_ca_system_score_gemma":0.001150947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003162769,"about_ca_topic_score_gemma":0.003435383,"domain_scores_codex":[0.9981441,0.001222056,0.00006470749,0.0001690092,0.0002789815,0.0001210265],"domain_scores_gemma":[0.998476,0.0009550338,0.0001353135,0.00008370143,0.0002617957,0.00008819941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000281926,0.0001564684,0.0005598424,0.0002172562,0.0001371555,0.0002351864,0.000559527,0.6576711,0.002280365,0.2949949,0.001723306,0.04118297],"study_design_scores_gemma":[0.00001043717,0.00003765802,0.00007204284,0.00001247946,0.00002177084,0.00001883389,0.00006356946,0.9397039,0.0002796894,0.05935583,0.0004077434,0.00001592679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03374728,0.0001564964,0.9608202,0.000322903,0.00004781691,0.0000522968,0.0001023506,0.00007265443,0.004678008],"genre_scores_gemma":[0.8565546,0.0001862427,0.1387232,0.00009025387,0.00003015665,0.0001574135,0.0001473509,0.00002976495,0.004081149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004069378,"threshold_uncertainty_score":0.01361346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3729088248077768,"score_gpt":0.4874063125129494,"score_spread":0.1144974877051726,"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."}}