{"id":"W3185287204","doi":"10.1002/int.22562","title":"A new method for deriving priority from dual hesitant fuzzy preference relations","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Consistency (knowledge bases); Preference; Dual (grammatical number); Preference relation; Computer science; Group decision-making; Fuzzy logic; Probabilistic logic; Property (philosophy); Basis (linear algebra); Data mining; Mathematical optimization; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004004312,0.001185978,0.001264062,0.003490403,0.0009988268,0.002455984,0.001475008,0.000923229,0.004329228],"category_scores_gemma":[0.009217139,0.0007231775,0.002152019,0.003010642,0.001125595,0.004258279,0.0017357,0.002414347,0.0009181389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001336953,"about_ca_system_score_gemma":0.001955727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001933515,"about_ca_topic_score_gemma":0.001605938,"domain_scores_codex":[0.9961509,0.001285641,0.0004272104,0.0006887836,0.001261214,0.0001862329],"domain_scores_gemma":[0.9969913,0.001370895,0.0002148018,0.0002420145,0.001069403,0.0001116194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000214056,0.0001225676,0.001354359,0.0007721019,0.0002537173,0.0003550431,0.001217142,0.09370637,0.01335816,0.3992816,0.004670258,0.4846947],"study_design_scores_gemma":[0.00008076298,0.0002099865,0.0005545808,0.0001078917,0.0001257286,0.0005773568,0.0002709041,0.7741618,0.008808322,0.1965791,0.01837118,0.0001523457],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009332993,0.00005602539,0.998018,0.00003567966,0.00002534408,0.00003495673,0.00002085835,0.00004747242,0.0008283028],"genre_scores_gemma":[0.0752599,0.0002577652,0.9216357,0.00007665676,0.00008849954,0.0002211028,0.0001383834,0.0000617847,0.002259999],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004329228,"threshold_uncertainty_score":0.02117711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2587212012644264,"score_gpt":0.4737449613594993,"score_spread":0.2150237600950729,"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."}}