{"id":"W2054476895","doi":"10.1007/s11238-009-9134-6","title":"Combining strength and uncertainty for preferences in the graph model for conflict resolution with multiple decision makers","year":2009,"lang":"en","type":"article","venue":"Theory and Decision","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"","keywords":"Preference; Status quo; Stability (learning theory); Computer science; Conflict resolution; Mathematical optimization; Management science; Operations research; Artificial intelligence; Microeconomics; Mathematics; Economics; Machine learning; Political science","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":[0.006946506,0.001405367,0.002115134,0.002235809,0.0008919686,0.003444871,0.002916132,0.002982316,0.004370212],"category_scores_gemma":[0.02758476,0.0009623189,0.001709589,0.002937656,0.002845399,0.0101313,0.002044186,0.003272859,0.0004731657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001918802,"about_ca_system_score_gemma":0.001061785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003104507,"about_ca_topic_score_gemma":0.003917589,"domain_scores_codex":[0.9942607,0.003963251,0.0001776597,0.000496624,0.0007723966,0.0003293925],"domain_scores_gemma":[0.9745428,0.02274519,0.0008719231,0.0006513276,0.0006667168,0.0005220902],"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":[0.0002618785,0.000099399,0.001190046,0.000180524,0.0001781592,0.0002010444,0.0004023175,0.5130451,0.0008905733,0.4590765,0.0007978891,0.02367661],"study_design_scores_gemma":[0.00003198933,0.00003343223,0.0001791133,0.00001450247,0.00004081548,0.00004260912,0.00005372569,0.5666021,0.0001374831,0.4325351,0.0002913772,0.00003775729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05559567,0.0002653872,0.9387915,0.0009029672,0.00004311368,0.00005365891,0.0001005117,0.00005634443,0.004190866],"genre_scores_gemma":[0.8570469,0.0005109211,0.1391843,0.0002320249,0.00009505606,0.0002048699,0.0001438813,0.00006297657,0.002519088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006946506,"threshold_uncertainty_score":0.03673708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0964554859682428,"score_gpt":0.3725000913649117,"score_spread":0.276044605396669,"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."}}