{"id":"W4367394512","doi":"10.1007/s11071-023-08506-7","title":"Marginalization in random permutation set theory: from the cooperative game perspective","year":2023,"lang":"en","type":"article","venue":"Nonlinear Dynamics","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Random permutation; Permutation (music); Mathematics; Cardinality (data modeling); Set (abstract data type); Perspective (graphical); Power set; Game theory; Function (biology); Random function; Probability theory; Permutation graph; Set function; Event (particle physics); Discrete mathematics; Combinatorics; Theoretical computer science; Computer science; Random variable; Mathematical economics; Symmetric group; Data mining; Statistics","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004477576,0.000193865,0.0003277834,0.0003629421,0.0001848484,0.0004918076,0.0007556199,0.0001177991,0.0005377625],"category_scores_gemma":[0.01241888,0.0001246091,0.0001040471,0.0024595,0.0001441144,0.0003681346,0.0002079639,0.0002719763,0.0009809817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002691203,"about_ca_system_score_gemma":0.0001563421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002232032,"about_ca_topic_score_gemma":0.002124382,"domain_scores_codex":[0.9960186,0.001221064,0.0006431135,0.0006244623,0.001219111,0.0002736889],"domain_scores_gemma":[0.9909564,0.007373394,0.0002261211,0.0006213517,0.000765568,0.00005719402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004468314,0.0004184527,0.09027617,0.00001017671,0.0002131112,0.0003560134,0.1703403,0.3345909,0.001577063,0.2587058,0.009317714,0.129726],"study_design_scores_gemma":[0.00137354,0.00002090268,0.02573587,0.000023807,0.000009592438,0.000002707404,0.02143167,0.8804635,0.00001558678,0.06945647,0.001321951,0.0001443629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8291932,0.00008494927,0.1638634,0.003500392,0.0007153142,0.0006487038,0.0006049728,0.0001223835,0.001266622],"genre_scores_gemma":[0.9948826,0.00003956045,0.002297454,0.0004901516,0.0002307434,0.0000297104,0.0004333793,0.00003513956,0.001561301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5458726,"threshold_uncertainty_score":0.9997969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1140828063444978,"score_gpt":0.4345320358023921,"score_spread":0.3204492294578943,"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."}}