{"id":"W4379507421","doi":"10.1007/978-3-031-30403-3_8","title":"Hybrid Multi-attribute Decision-Making Methods Based on Preferential Voting","year":2023,"lang":"en","type":"book-chapter","venue":"Studies in systems, decision and control","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Voting; Computer science; Process (computing); Artificial intelligence; Data mining; 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":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.02541376,0.001652086,0.004829744,0.003990543,0.0009063256,0.001425464,0.00237718,0.0008237531,0.0003567249],"category_scores_gemma":[0.05883827,0.001222471,0.0008983354,0.0006300102,0.0005151561,0.0003376371,0.001716823,0.001476335,0.001195014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005243832,"about_ca_system_score_gemma":0.0002193524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001452767,"about_ca_topic_score_gemma":0.0001031286,"domain_scores_codex":[0.980779,0.001743245,0.006340051,0.003730812,0.006170756,0.001236126],"domain_scores_gemma":[0.902667,0.08993565,0.00247708,0.002507037,0.002044112,0.0003690547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002014608,0.0001432139,0.0008425598,0.0001710722,0.0006023017,0.001193473,0.0005698875,0.0106949,0.0000353533,0.008042299,0.02497911,0.9507113],"study_design_scores_gemma":[0.02056064,0.000740109,0.002648914,0.03332501,0.0005521203,0.0001932955,0.003106765,0.6524532,0.00001157906,0.07599313,0.2060633,0.004351846],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009507482,0.01410856,0.9484116,0.0001844744,0.02177738,0.003732621,0.0008521072,0.0004287917,0.009553667],"genre_scores_gemma":[0.9016806,0.0008272035,0.04063909,0.0008895042,0.001289817,0.0003665684,0.00002376968,0.000465251,0.05381817],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9463594,"threshold_uncertainty_score":0.9996226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3180020934915572,"score_gpt":0.5070131577339035,"score_spread":0.1890110642423463,"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."}}