{"id":"W3121880336","doi":"","title":"How to divide things fairly","year":2014,"lang":"en","type":"article","venue":"Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Minimax; Rank (graph theory); Pareto optimal; Simple (philosophy); Property (philosophy); Mathematical economics; Pareto principle; Computer science; Microeconomics; Economics; Mathematical optimization; Mathematics; Combinatorics; Multi-objective optimization; Machine learning","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":[0.004226323,0.0008252587,0.001111668,0.0007510172,0.002343084,0.003472748,0.001926055,0.002300579,0.01993884],"category_scores_gemma":[0.01620915,0.0004578295,0.0008725047,0.001205297,0.003414364,0.007578683,0.002912049,0.00244439,0.004365525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002173552,"about_ca_system_score_gemma":0.002559107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002597774,"about_ca_topic_score_gemma":0.00234429,"domain_scores_codex":[0.9962358,0.001521517,0.000200053,0.0009028229,0.0007118207,0.0004279641],"domain_scores_gemma":[0.9947184,0.00225887,0.0004754087,0.001683852,0.0005588222,0.0003046466],"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":[0.0003185114,0.0001444147,0.001220264,0.0001374884,0.0001133111,0.00008529808,0.0006159681,0.05483532,0.003194773,0.7919872,0.01449173,0.1328557],"study_design_scores_gemma":[0.00007733813,0.00006354428,0.0002653123,0.00004064213,0.00002520208,0.00006168269,0.0002021024,0.07462093,0.001286042,0.8995809,0.02375568,0.00002065307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06775328,0.0005329097,0.847456,0.01209117,0.0003182344,0.0004932357,0.0002997903,0.0006576535,0.07039768],"genre_scores_gemma":[0.5030476,0.0004266063,0.4320223,0.002337988,0.0002392474,0.0008675753,0.0004389937,0.0007010137,0.05991878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01993884,"threshold_uncertainty_score":0.06670201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02009124808011712,"score_gpt":0.1729502117112033,"score_spread":0.1528589636310862,"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."}}