{"id":"W2395929104","doi":"","title":"A fuzzy-based inference mechanism of trust for improved social recommenders.","year":2012,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Vagueness; Computer science; Recommender system; Collaborative filtering; Inference; Context (archaeology); Fuzzy logic; Artificial intelligence; Fuzzy inference; Machine learning; Mechanism (biology); Data mining; Information retrieval; Fuzzy control system; Adaptive neuro fuzzy inference system","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":[0.0005747262,0.000127532,0.0002286288,0.00009198592,0.00009542048,0.00004497256,0.0005156738,0.00009945818,0.00001661437],"category_scores_gemma":[0.00002431375,0.0001069976,0.0001226561,0.00015023,0.00001575588,0.0003728674,0.0001075771,0.00006568401,0.000001790932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003168025,"about_ca_system_score_gemma":0.00005789283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004890077,"about_ca_topic_score_gemma":0.000005236589,"domain_scores_codex":[0.9990254,0.00004779923,0.000288568,0.0001897405,0.0001194737,0.0003290048],"domain_scores_gemma":[0.9992498,0.000119762,0.0001615321,0.0003024847,0.00009339331,0.00007305254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006326102,0.000114413,0.0001394045,0.00004512946,0.00001451767,5.396501e-8,0.0005325865,6.760815e-8,0.003093185,0.942574,0.00420639,0.04927398],"study_design_scores_gemma":[0.003470432,0.001034788,0.0009299484,0.00008112201,0.00004327427,0.000007825308,0.0006341363,0.08303221,0.4566948,0.4028186,0.04984881,0.00140406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004192744,0.0000148538,0.9859889,0.002266139,0.0003788674,0.0003913152,0.000005723351,0.0002392804,0.01029563],"genre_scores_gemma":[0.7906218,0.000001405958,0.2085412,0.0005569108,0.00007839007,0.00009250749,0.000002041932,0.000007866985,0.00009786288],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7902026,"threshold_uncertainty_score":0.4363238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05181319023210568,"score_gpt":0.3023928315768289,"score_spread":0.2505796413447233,"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."}}