{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008253896,0.000173969,0.0002705085,0.0002035158,0.0005242083,0.0002215641,0.0004301929,0.00009368969,0.000006842977],"category_scores_gemma":[0.002271311,0.0000923734,0.0000625107,0.0003848047,0.0002218839,0.0002568412,0.00004159025,0.0001200729,0.000001909862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009918321,"about_ca_system_score_gemma":0.0000299633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003624092,"about_ca_topic_score_gemma":0.00007971173,"domain_scores_codex":[0.9980699,0.0002339207,0.0004708226,0.0005254313,0.0004516474,0.0002482794],"domain_scores_gemma":[0.977971,0.02117135,0.0001656984,0.0004546832,0.0001580625,0.00007918899],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.007780202,0.000121573,0.0003166714,0.000003051591,0.000005720929,4.726201e-7,0.002939282,0.01269459,0.0002012527,0.4565148,0.0003732704,0.5190491],"study_design_scores_gemma":[0.00179476,0.0004120432,0.003553537,0.00005212256,0.00001585768,0.000005864615,0.002625055,0.1652237,0.00005898362,0.8254781,0.0006597779,0.0001201527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5705466,0.0001599825,0.4283013,0.0001446205,0.00001821528,0.0006027202,0.00003479608,0.00001344422,0.0001783552],"genre_scores_gemma":[0.9838756,0.00006006389,0.01551997,0.0003391201,0.00002031292,0.0001042495,0.00001141344,0.000006614517,0.00006262951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5189289,"threshold_uncertainty_score":0.4031839,"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."}}