{"id":"W4394896937","doi":"10.1109/tmc.2024.3390208","title":"ProSecutor: Protecting Mobile AIGC Services on Two-Layer Blockchain via Reputation and Contract Theoretic Approaches","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Blockchain; Computer science; Computer security; Reputation; Layer (electronics); Reputation management; Computer network; Law; Chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008575551,0.0003098914,0.0002629664,0.0003350149,0.0007953796,0.0003488342,0.0004743588,0.0001970964,0.000009564195],"category_scores_gemma":[0.000004029955,0.0002887787,0.0001081274,0.0007192585,0.0001339873,0.0001650222,0.00001658503,0.000923553,0.00003178348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008887773,"about_ca_system_score_gemma":0.00004323979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004206557,"about_ca_topic_score_gemma":0.00001333139,"domain_scores_codex":[0.9977806,0.0001710507,0.0004202515,0.000974162,0.0002569165,0.0003970019],"domain_scores_gemma":[0.9985763,0.00051113,0.0001218483,0.0006353433,0.00006382744,0.00009149215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001701799,0.0003333868,0.00001048501,0.0002499336,0.00007566297,0.00001609123,0.005053885,0.1592011,0.003454196,0.01653013,0.000003017636,0.8150551],"study_design_scores_gemma":[0.0002883897,0.0003608774,0.00001789916,0.0001893539,0.0000256255,0.00009952799,0.0003311089,0.9599026,0.03372246,0.004586471,0.000182477,0.0002932533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.343564,0.0002917059,0.6534083,0.0001594468,0.0002670736,0.0011748,0.000004882787,0.00100453,0.0001253157],"genre_scores_gemma":[0.989383,0.00001374563,0.009485649,0.0001173814,0.00007875551,0.0008573481,0.000001776174,0.00003443818,0.00002786829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8147618,"threshold_uncertainty_score":0.9999564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01424477012339462,"score_gpt":0.2520721446569496,"score_spread":0.237827374533555,"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."}}