{"id":"W1500791855","doi":"10.1007/11564751_90","title":"Mechanism Design for Preference Aggregation over Coalitions","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Impossibility; Computer science; Mechanism (biology); Preference; Mechanism design; Outcome (game theory); Rationality; Context (archaeology); Mathematical economics; Theoretical computer science; Artificial intelligence; Microeconomics; Mathematics; Economics; Epistemology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001137998,0.0005392385,0.0004789656,0.0005982942,0.0004836665,0.0006283129,0.002924068,0.0004125985,0.0000451843],"category_scores_gemma":[0.0001848245,0.0004859288,0.0001761309,0.0004299814,0.0003618645,0.0008233349,0.0007927741,0.0005006148,0.00006184244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003855271,"about_ca_system_score_gemma":0.0007672294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009807087,"about_ca_topic_score_gemma":0.00007057813,"domain_scores_codex":[0.9963315,0.00005071388,0.0004881566,0.001583684,0.0007346242,0.000811299],"domain_scores_gemma":[0.9969954,0.0008747588,0.0003340377,0.00119475,0.0004051068,0.0001959275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006709399,0.00003877474,0.000004128035,0.00003064524,0.00001096902,0.000009731543,0.0007147855,0.008629948,0.0001176972,0.6169048,0.0001150197,0.3734168],"study_design_scores_gemma":[0.000279801,0.0001905794,0.00002309225,0.0002076683,0.00001018138,0.00002597705,7.559062e-8,0.4343229,0.002383452,0.559726,0.002342346,0.0004878839],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001178107,0.0003819515,0.9918914,0.0003697652,0.001620934,0.0009722089,0.000012192,0.0002451426,0.004494635],"genre_scores_gemma":[0.08064268,0.00008459675,0.9148617,0.001175962,0.0009987426,0.00008714072,0.00001444367,0.00004326404,0.002091426],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.425693,"threshold_uncertainty_score":0.9997593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04829329954142331,"score_gpt":0.2607175010341069,"score_spread":0.2124242014926836,"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."}}