{"id":"W4381857247","doi":"10.1007/s42979-023-01850-w","title":"An Efficient Graph Mining Approach Using Evidence Based Fuzzy Soft Set Method","year":2023,"lang":"en","type":"article","venue":"SN Computer Science","topic":"Fuzzy and Soft Set Theory","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sheridan College","funders":"","keywords":"Centrality; Graph; Credibility; Computer science; Data mining; Adjacency matrix; Fuzzy set; Node (physics); Rank (graph theory); Pairwise comparison; Fuzzy logic; Theoretical computer science; Mathematics; Artificial intelligence; Combinatorics; Engineering","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":[0.001183453,0.0006051995,0.00162746,0.005142323,0.0008318468,0.001971351,0.001813768,0.001051673,0.004056218],"category_scores_gemma":[0.004504795,0.0005015033,0.001300591,0.003092862,0.0004494907,0.001764697,0.001240404,0.001117641,0.0008637926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005573316,"about_ca_system_score_gemma":0.001568748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002650759,"about_ca_topic_score_gemma":0.004330546,"domain_scores_codex":[0.998632,0.0003045448,0.0001031886,0.0001932139,0.0006998242,0.00006716502],"domain_scores_gemma":[0.9970673,0.001811214,0.0001541511,0.0002138334,0.0006816941,0.0000718747],"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":[0.0002241711,0.0003768566,0.002054489,0.0005510038,0.0003237822,0.0003499328,0.000135778,0.1200143,0.00950053,0.04118465,0.003993833,0.8212906],"study_design_scores_gemma":[0.00002490655,0.00005590309,0.0004997288,0.00003898651,0.0000908875,0.0001828438,0.0000510124,0.9662635,0.003109187,0.02747542,0.002183488,0.00002415112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00666552,0.0001833051,0.9914842,0.0001185969,0.00003046409,0.0001061779,0.0001189827,0.0002648732,0.001027789],"genre_scores_gemma":[0.1050964,0.0002329667,0.892556,0.0000595576,0.00005138712,0.0001435489,0.0002892096,0.00003590014,0.001535029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005142323,"threshold_uncertainty_score":0.01356941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2952049281002482,"score_gpt":0.4514064897539203,"score_spread":0.156201561653672,"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."}}