{"id":"W2114645979","doi":"10.1145/1501434.1501460","title":"Modeling trust using transactional, numerical units","year":2006,"lang":"en","type":"article","venue":"","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Honesty; Database transaction; Computer science; Incentive; Trustworthiness; Computer security; Profit (economics); Variety (cybernetics); Transaction processing; Business; Internet privacy; Microeconomics; Economics","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":[0.002365996,0.0005684984,0.0005174571,0.0008001819,0.0006577182,0.002802245,0.001588436,0.001717379,0.004149102],"category_scores_gemma":[0.01117742,0.0003893436,0.0007090664,0.001048915,0.002163334,0.007518074,0.001569453,0.001457071,0.0006540711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483072,"about_ca_system_score_gemma":0.0009273191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003636362,"about_ca_topic_score_gemma":0.001970012,"domain_scores_codex":[0.9983216,0.000886548,0.0001351953,0.0001813802,0.0003558893,0.0001194712],"domain_scores_gemma":[0.9952022,0.002514936,0.0008975544,0.0007415874,0.0004104138,0.0002333477],"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":[0.0001122863,0.00005765453,0.002322509,0.00004469905,0.00004503623,0.0001804943,0.0003416953,0.4918147,0.00123674,0.4939918,0.0005264084,0.009326061],"study_design_scores_gemma":[0.00001754976,0.00004199081,0.0001967228,0.00001298316,0.00001233947,0.00003176096,0.00004859827,0.9001278,0.0003419022,0.09740827,0.001747742,0.00001237204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1045205,0.0003484317,0.8787524,0.001023849,0.0001028968,0.0001393072,0.0001903699,0.0002983991,0.01462396],"genre_scores_gemma":[0.9267702,0.0003843832,0.06693931,0.00007785304,0.00005084464,0.0001980463,0.00009421378,0.00004365715,0.005441434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004149102,"threshold_uncertainty_score":0.01388013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02687063550899704,"score_gpt":0.2436352663109095,"score_spread":0.2167646308019124,"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."}}