{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006542399,0.00006082697,0.0000655449,0.00006297751,0.0001548897,0.00003102195,0.0003278319,0.00007121143,0.00002039887],"category_scores_gemma":[0.000002109365,0.00005705671,0.00002138674,0.0005504845,0.00002180644,0.0001161836,0.0000299128,0.0001020241,0.0000122574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002040224,"about_ca_system_score_gemma":0.00003595443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003228105,"about_ca_topic_score_gemma":0.00001056482,"domain_scores_codex":[0.9994488,0.000009858926,0.000120092,0.0001951148,0.00009025392,0.0001359216],"domain_scores_gemma":[0.9996299,0.00001146572,0.00001403833,0.0002609798,0.00006118765,0.00002239427],"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":[6.088574e-7,0.00005709471,0.00007779792,0.000001329515,0.0000033651,0.000001355525,0.00002206748,0.07803982,0.0005612657,0.916825,0.00008958419,0.004320696],"study_design_scores_gemma":[0.0000666627,0.000004559715,0.0000272468,9.873211e-7,0.000001792112,0.00001825786,0.000008532082,0.9681008,0.0008163936,0.03003891,0.0008439639,0.00007191822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0853382,0.00004316457,0.9119861,0.0007628796,0.00003294569,0.00004601052,5.743034e-7,0.000314313,0.001475869],"genre_scores_gemma":[0.8680059,0.000001294047,0.1317896,0.00009146799,0.00002181657,0.000005895675,9.220796e-7,0.000002959984,0.00008018174],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.890061,"threshold_uncertainty_score":0.2326705,"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."}}