{"id":"W2022437281","doi":"10.3390/axioms3010050","title":"A Hybrid Artificial Reputation Model Involving Interaction Trust, Witness Information and the Trust Model to Calculate the Trust Value of Service Providers","year":2014,"lang":"en","type":"article","venue":"Axioms","topic":"Access Control and Trust","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reputation; Witness; Service provider; Service (business); Computer science; Computational trust; Value (mathematics); Sample (material); Business; Trustworthiness; Internet privacy; Marketing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001394984,0.0001237775,0.0001859793,0.00008359588,0.0006571722,0.000273366,0.0002700304,0.00006311956,0.000005654772],"category_scores_gemma":[0.0005048551,0.00007873766,0.00005432883,0.0003038266,0.0002453454,0.001585615,0.0000718056,0.0001433086,0.000007859604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007938642,"about_ca_system_score_gemma":0.0001851319,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01168665,"about_ca_topic_score_gemma":0.001763529,"domain_scores_codex":[0.998607,0.000208978,0.0004063809,0.0001639152,0.0003931763,0.0002205353],"domain_scores_gemma":[0.9989617,0.0001864588,0.0002909255,0.0002126204,0.0002786157,0.00006961181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003768067,0.00002071493,0.00007805279,0.00003533889,0.00002870665,1.46154e-7,0.08301276,0.4603669,0.0001291185,0.4168574,0.00003928426,0.03905478],"study_design_scores_gemma":[0.0005036941,0.00001676077,0.0004447387,0.00002247933,0.0000487669,9.883209e-7,0.004433834,0.9598055,0.0001147173,0.03431122,0.0001950649,0.0001022682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7732027,0.00001914481,0.2139386,0.009761415,0.0001666964,0.0006753413,0.000006596641,0.000044777,0.002184742],"genre_scores_gemma":[0.9977066,0.0000102225,0.0001474614,0.001819003,0.0001162644,0.00007240057,0.000009515076,0.000009058063,0.0001094545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4994386,"threshold_uncertainty_score":0.9948946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02047182825374607,"score_gpt":0.2814902819031714,"score_spread":0.2610184536494253,"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."}}