{"id":"W4386304139","doi":"10.32920/24058713.v1","title":"Multi-Criteria Decision-Making Approach with Interval-Valued Intuitionistic Fuzzy Assessment for Green Supplier Evaluation and Selection","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"TOPSIS; Ideal solution; Supply chain; Selection (genetic algorithm); Multiple-criteria decision analysis; Fuzzy logic; Computer science; Fuzzy set; Preference; Set (abstract data type); Similarity (geometry); Cosine similarity; Interval (graph theory); Operations research; Management science; Mathematics; Artificial intelligence; Economics; Business; Marketing; 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":[0.006503758,0.001593021,0.001435191,0.002798299,0.001223685,0.002713666,0.001689944,0.001178833,0.002758816],"category_scores_gemma":[0.006511715,0.0006296887,0.002224988,0.002679829,0.001173076,0.001713038,0.001661982,0.001823289,0.0003160911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002795698,"about_ca_system_score_gemma":0.002918761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00364998,"about_ca_topic_score_gemma":0.004497473,"domain_scores_codex":[0.9942663,0.003180684,0.0003093928,0.0003593754,0.001687477,0.0001968373],"domain_scores_gemma":[0.9975778,0.001406139,0.000237561,0.00008388493,0.00057552,0.0001189635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002059807,0.000259964,0.001612841,0.0009055762,0.0004283611,0.0006887504,0.001070134,0.7495191,0.005902225,0.1274043,0.002063109,0.1099397],"study_design_scores_gemma":[0.00002809623,0.0001337958,0.0003447148,0.0001005761,0.0000743612,0.00007937737,0.0001501171,0.9543609,0.0009307787,0.04194273,0.001809108,0.00004534382],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006596803,0.000275322,0.9895235,0.0001328558,0.00003005451,0.0001467426,0.0000318756,0.00004248036,0.003220441],"genre_scores_gemma":[0.3043143,0.0004871775,0.6930429,0.00009029255,0.00005029752,0.0005965754,0.00009699188,0.0000176639,0.00130386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006503758,"threshold_uncertainty_score":0.03439558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2623034250957873,"score_gpt":0.5020117647112315,"score_spread":0.2397083396154442,"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."}}