{"id":"W4407755337","doi":"10.7717/peerj-cs.2555","title":"The technique of fuzzy analytic hierarchy process (FAHP) based on the triangular q-rung fuzzy numbers (TR-q-ROFNS) with applications in best African coffee brand selection","year":2025,"lang":"en","type":"article","venue":"PeerJ Computer Science","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"King Saud University","keywords":"Selection (genetic algorithm); Fuzzy logic; Hierarchy; Fuzzy number; Mathematics; Analytic hierarchy process; Computer science; Operations research; Fuzzy set; Economics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009241509,0.0002348305,0.0003816095,0.001224243,0.001023416,0.0008703336,0.00315132,0.00006362527,0.00001625723],"category_scores_gemma":[0.001420783,0.0001214773,0.0001000436,0.01242166,0.001107573,0.0003952394,0.0002688603,0.0003359043,0.00001267394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000158468,"about_ca_system_score_gemma":0.0007865703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008119048,"about_ca_topic_score_gemma":0.0002200193,"domain_scores_codex":[0.9947925,0.0003864632,0.0008310918,0.0009896226,0.00253357,0.0004667834],"domain_scores_gemma":[0.9924343,0.004642291,0.0004201839,0.00133745,0.001059385,0.0001064193],"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":[0.001720369,0.00213819,0.08698995,0.0001599462,0.0001030293,0.000041544,0.008122775,0.2610414,0.02674161,0.1170769,0.004810071,0.4910542],"study_design_scores_gemma":[0.001304015,0.0003152438,0.03264581,0.0003392451,0.00003238863,0.00001755364,0.001257491,0.9080888,0.007868724,0.04313627,0.00455727,0.0004371703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1120271,0.00004481893,0.8756641,0.004559378,0.0002378994,0.002037092,0.000008597503,0.00006632855,0.005354708],"genre_scores_gemma":[0.9821155,0.000001754161,0.01703253,0.0003196842,0.00003673343,0.0002467003,7.752529e-7,0.000009688857,0.0002366011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8700885,"threshold_uncertainty_score":0.8392647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04486780936093245,"score_gpt":0.377613295597296,"score_spread":0.3327454862363636,"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."}}