{"id":"W4414976223","doi":"10.13033/ijahp.v17i3.1311","title":"FUZZY ANALYTIC HIERARCHY PROCESS: A COMPREHENSIVE LITERATURE REVIEW","year":2025,"lang":"en","type":"article","venue":"International Journal of the Analytic Hierarchy Process","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Hierarchy; Fuzzy logic; Fuzzy set; Outcome (game theory); Set (abstract data type); Process (computing)","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":[],"consensus_categories":[],"category_scores_codex":[0.0004882022,0.0002646635,0.0004736503,0.0006573708,0.0001970809,0.0003756416,0.00395369,0.00007565186,0.00002470165],"category_scores_gemma":[0.0004823034,0.0001724292,0.0003414033,0.002907558,0.0001330447,0.001321116,0.0003935006,0.0006379941,0.00002183841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001713241,"about_ca_system_score_gemma":0.0009754492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002248506,"about_ca_topic_score_gemma":0.000001959046,"domain_scores_codex":[0.9969654,0.0001130386,0.0009491992,0.0003417754,0.001339888,0.0002906604],"domain_scores_gemma":[0.9945711,0.0001456477,0.000702769,0.0004627053,0.003992965,0.0001247977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001655175,0.005215086,0.1054478,0.03406928,0.01567315,0.005338098,0.02745451,0.08674813,0.002326268,0.2466249,0.2322486,0.237199],"study_design_scores_gemma":[0.007744587,0.0007383605,0.03144046,0.1031732,0.001404971,0.01184198,0.0006023907,0.08534592,0.00835797,0.641543,0.105032,0.002775206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2053446,0.2172759,0.1372684,0.4003043,0.01341823,0.002355126,0.0001178197,0.000425566,0.02349017],"genre_scores_gemma":[0.9729797,0.008796123,0.001321375,0.01373439,0.0004907294,0.00001155173,0.000008148272,0.00001931092,0.002638663],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7676352,"threshold_uncertainty_score":0.7347006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008081533139539396,"score_gpt":0.300531492824905,"score_spread":0.2924499596853656,"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."}}