{"id":"W3199905177","doi":"10.1007/978-3-030-87334-9_25","title":"3RD: A Multi-criteria Decision-Making Method Based on Three-Way Rankings","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"ELECTRE; Multiple-criteria decision analysis; Ranking (information retrieval); Computer science; Set (abstract data type); Dominance (genetics); Decision theory; Prospect theory; Construct (python library); Data mining; Operations research; Artificial intelligence; Mathematics; 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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002054657,0.0008667966,0.0009502966,0.001167462,0.0004874872,0.001574918,0.00495583,0.0005175934,0.0001131135],"category_scores_gemma":[0.0003510765,0.0007261443,0.000347564,0.001164221,0.000414025,0.0005147147,0.00191321,0.001225162,0.00005946174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003524412,"about_ca_system_score_gemma":0.0006569664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001790571,"about_ca_topic_score_gemma":0.000118004,"domain_scores_codex":[0.9935029,0.0001103582,0.0007748813,0.002887363,0.001729578,0.0009949071],"domain_scores_gemma":[0.9937957,0.002612994,0.0003894186,0.002630633,0.0003496671,0.0002215802],"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":[0.00001564965,0.00006100453,0.00002028763,0.00002669408,0.000009293125,0.0004562291,0.0002469067,0.06144576,0.00003225405,0.005820266,0.00003345307,0.9318322],"study_design_scores_gemma":[0.0004808955,0.0001850521,0.000173561,0.001399526,0.00000932392,0.0000722224,1.05577e-7,0.9006999,0.0001208512,0.09476598,0.001302825,0.0007897326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002042049,0.000415959,0.9915307,0.0006718653,0.003260583,0.0004512741,0.000008610989,0.000221762,0.00341885],"genre_scores_gemma":[0.03990755,0.00001277206,0.9532779,0.006264,0.0004206245,0.00001288203,0.000004941125,0.00005178973,0.00004755077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9310425,"threshold_uncertainty_score":0.999519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02970775580578248,"score_gpt":0.3068965114222851,"score_spread":0.2771887556165026,"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."}}