{"id":"W1484854956","doi":"","title":"Dynamic Trust Applied to Ad Hoc Network Resources","year":2003,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science; Computational trust; Delegation; Subjective logic; Trustworthiness; Dynamic network analysis; Trust management (information system); Resource (disambiguation); Knowledge management; Computer security; Reputation; Artificial intelligence; Computer network","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":[0.003591447,0.0004381525,0.0004073125,0.0007694,0.001325163,0.003038888,0.0009772251,0.0008091778,0.001555747],"category_scores_gemma":[0.01959083,0.0003697889,0.0003925745,0.0007774761,0.00258583,0.004807731,0.00291939,0.001123941,0.0002069613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003051178,"about_ca_system_score_gemma":0.001777687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007797447,"about_ca_topic_score_gemma":0.003479401,"domain_scores_codex":[0.9954571,0.002315435,0.0003017764,0.0005504022,0.001078567,0.0002968288],"domain_scores_gemma":[0.9916478,0.004405102,0.0009731823,0.001498468,0.001071674,0.0004036821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004289426,0.0001442511,0.007753459,0.0004049973,0.00008491318,0.0009016382,0.007330658,0.2123849,0.01092381,0.6179587,0.00249248,0.1391913],"study_design_scores_gemma":[0.00006917572,0.0002510892,0.001811344,0.00008247625,0.00006485351,0.0004241978,0.001832284,0.7462744,0.008825955,0.2192482,0.0210286,0.00008744447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2230166,0.0006022414,0.7384882,0.001560544,0.0001576695,0.0003064297,0.00009158748,0.0005873442,0.03518935],"genre_scores_gemma":[0.9506711,0.0001357585,0.04755616,0.0000438231,0.00001399684,0.0000558027,0.00002404833,0.00002382126,0.001475392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007797447,"threshold_uncertainty_score":0.02213794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589792386627851,"score_gpt":0.2178758341298171,"score_spread":0.2019779102635386,"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."}}