{"id":"W4407236541","doi":"10.36548/jscp.2024.4.007","title":"A Scalable and Secure Data Analytics Framework for Decentralized Autonomous Healthcare Systems using Fuzzy Logic, Blockchain Sharding, Dynamic Network Slicing, and ECC","year":2025,"lang":"en","type":"article","venue":"Journal of Soft Computing Paradigm","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"PotashCorp (Canada)","funders":"","keywords":"Blockchain; Scalability; Slicing; Computer science; Fuzzy logic; Distributed computing; Computer security; Database; Artificial intelligence; World Wide Web","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":[0.0008787405,0.0002841132,0.0003957336,0.0004203191,0.0006279534,0.001133147,0.0007601673,0.0006049803,0.001712107],"category_scores_gemma":[0.001043861,0.0001529574,0.0003581053,0.0003469368,0.0007095102,0.001513038,0.00128354,0.0008374031,0.000348708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009169399,"about_ca_system_score_gemma":0.002385925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003458853,"about_ca_topic_score_gemma":0.00412754,"domain_scores_codex":[0.9995375,0.00008236378,0.00003686031,0.00007272364,0.0002042454,0.00006645652],"domain_scores_gemma":[0.9995326,0.0001173365,0.00005126911,0.0001023159,0.0001328989,0.00006364536],"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":[0.0003491206,0.0002582469,0.002963369,0.0001881855,0.00009747446,0.0007663075,0.0004688605,0.4853582,0.04628094,0.2358812,0.007130749,0.2202572],"study_design_scores_gemma":[0.00002695306,0.00008036658,0.0002731774,0.00002356349,0.00001697354,0.0001099067,0.00004760591,0.9472318,0.007698318,0.03783551,0.0066337,0.00002219973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03349775,0.000215934,0.9602625,0.0007191243,0.00005543866,0.0001525011,0.0001072248,0.0009202057,0.004069372],"genre_scores_gemma":[0.7973905,0.0003229927,0.1977677,0.0001977177,0.00005616734,0.0001616975,0.0002230441,0.00004374868,0.003836365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003458853,"threshold_uncertainty_score":0.006877422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03607975417298814,"score_gpt":0.3231184689491979,"score_spread":0.2870387147762098,"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."}}