{"id":"W4244499999","doi":"10.32920/ryerson.14654145","title":"Secure Data Deduplication in Cloud Environments","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Cloud Data Security Solutions","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Data deduplication; Computer science; Cloud computing; Upload; Cloud storage; Encryption; Computer security; Service provider; Data security; Database; Computer network; Service (business); 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":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0003801435,0.0002038761,0.0002224118,0.000105406,0.0000525285,0.0003440334,0.005580284,0.0002549865,0.00008181295],"category_scores_gemma":[0.00009049949,0.0002332732,0.00004303817,0.0002734916,0.00003665014,0.0005300469,0.02380806,0.0006486687,0.0001356485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001779774,"about_ca_system_score_gemma":0.0002198518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005694377,"about_ca_topic_score_gemma":0.001360203,"domain_scores_codex":[0.9974914,0.0001116659,0.0003577591,0.001417807,0.0003524424,0.0002689467],"domain_scores_gemma":[0.9925312,0.00005964255,0.0001250255,0.007181356,0.00001551076,0.00008730916],"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":[0.00001315249,0.005249091,0.01260364,0.0006915737,0.0004469968,0.0004613355,0.01389049,0.01026451,0.002671242,0.5180652,0.3507976,0.08484521],"study_design_scores_gemma":[0.0004953279,0.00001515462,0.0176529,0.0002186216,0.00003080776,0.00003450192,0.000170727,0.8061585,0.0005079924,0.01438936,0.1592301,0.001096024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01033389,0.0007035462,0.9822576,0.003671781,0.001054337,0.0004171217,0.0002844287,0.0001303544,0.001146911],"genre_scores_gemma":[0.6630088,0.0008513349,0.3183455,0.001705897,0.0004154282,0.0001403062,0.01496245,0.00003787572,0.0005323749],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.795894,"threshold_uncertainty_score":0.9998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05321095790573612,"score_gpt":0.2944929288965459,"score_spread":0.2412819709908098,"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."}}