{"id":"W4403165669","doi":"10.61091/ars-160-13","title":"Properties of Cubic Fuzzy Competition Graphs with Applications","year":2024,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Competition (biology); Fuzzy logic; Cubic graph; Discrete mathematics; Computer science; Artificial intelligence; Graph; Line graph; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001163194,0.0001578762,0.0002937304,0.0004932469,0.0001343329,0.0003751889,0.0006751881,0.00006623832,0.0001650878],"category_scores_gemma":[0.0002544227,0.0001028915,0.0001036561,0.001706962,0.000208933,0.0004036121,0.000131139,0.0001534631,0.000470481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000342431,"about_ca_system_score_gemma":0.000100119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001916982,"about_ca_topic_score_gemma":0.000009368475,"domain_scores_codex":[0.9971967,0.0001382293,0.0006257267,0.0005177603,0.001320915,0.0002006524],"domain_scores_gemma":[0.997974,0.0005323511,0.0001484466,0.0007787013,0.0004808565,0.00008558414],"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":[0.00002759839,0.00008006761,0.000828417,0.00003112929,0.00002095511,0.000006686601,0.0003538089,0.00002407127,0.01066952,0.9784867,0.00123049,0.008240582],"study_design_scores_gemma":[0.0003633249,0.00009331227,0.001612781,0.0002379407,0.00002116174,0.00001892136,0.0003981149,0.001429235,0.006757465,0.9724717,0.01640886,0.0001871984],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854046,0.001487093,0.002763928,0.0004868533,0.001466072,0.0006119176,0.00001902439,0.0001934846,0.007567037],"genre_scores_gemma":[0.9982041,0.00001305397,0.001216392,0.00004240675,0.00001055945,0.00009934479,0.000003039671,0.00002197145,0.0003892047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01517837,"threshold_uncertainty_score":0.6047238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07967434188132747,"score_gpt":0.3477893823043242,"score_spread":0.2681150404229967,"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."}}