{"id":"W3201288682","doi":"10.1002/int.22676","title":"EviChain: A scalable blockchain for accountable intelligent surveillance systems","year":2021,"lang":"en","type":"article","venue":"International Journal of Intelligent Systems","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Scalability; Computer security; Byzantine fault tolerance; Context (archaeology); Overhead (engineering); Cryptography; Block (permutation group theory); Blockchain; Authentication (law); Distributed computing; Tamper resistance; Process (computing); Exploit; Vulnerability (computing); Embedded system; Fault tolerance; Database; Operating system","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":[0.001286709,0.000507595,0.0006871222,0.0004425499,0.0009092413,0.0009821665,0.001418615,0.0008431841,0.00742275],"category_scores_gemma":[0.003065048,0.0002371631,0.0002856538,0.0007117128,0.0007426685,0.002023756,0.002385556,0.0008803051,0.0008640568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008183717,"about_ca_system_score_gemma":0.00218182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003944324,"about_ca_topic_score_gemma":0.005294946,"domain_scores_codex":[0.9991961,0.000251831,0.00004513304,0.0001055389,0.000238177,0.0001631934],"domain_scores_gemma":[0.9985498,0.0004748627,0.0001261058,0.0004120886,0.0002092548,0.0002279755],"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":[0.001169151,0.0003596992,0.002331245,0.0004292884,0.00009233313,0.0007747819,0.0003789409,0.7009827,0.01507349,0.07732003,0.01139714,0.1896912],"study_design_scores_gemma":[0.0001867288,0.0001919263,0.0002226096,0.00002989445,0.00001558339,0.0001053452,0.00005215827,0.9546776,0.003768649,0.03115728,0.009573314,0.00001890659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1367957,0.001161381,0.8368678,0.001203444,0.0003016813,0.0008070794,0.0007399378,0.005110442,0.01701249],"genre_scores_gemma":[0.9211209,0.0003786765,0.07134135,0.0001206687,0.00003993783,0.0003431775,0.000483559,0.00008661467,0.006085119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00742275,"threshold_uncertainty_score":0.02483153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112965990049477,"score_gpt":0.280248707412957,"score_spread":0.2591190475124622,"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."}}