{"id":"W2618071483","doi":"10.1007/978-3-319-53817-4_10","title":"Deduplication Practices for Multimedia Data in the Cloud","year":2017,"lang":"en","type":"book-chapter","venue":"Studies in big data","topic":"Advanced Steganography and Watermarking Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Data deduplication; Computer science; Cloud computing; Encryption; Big data; Redundancy (engineering); Database; World Wide Web; Computer security; Data mining; 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":[],"category_scores_codex":[0.001958181,0.0002468037,0.0003253996,0.0001598881,0.0002490991,0.0001400844,0.01322997,0.0001394461,2.728789e-7],"category_scores_gemma":[0.00107727,0.0001745322,0.00003015958,0.00004382597,0.0002657713,0.001161802,0.007266123,0.0003671177,0.000003687968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002768428,"about_ca_system_score_gemma":0.00004894551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005329234,"about_ca_topic_score_gemma":0.001114132,"domain_scores_codex":[0.9980981,0.00004657602,0.000346821,0.001023508,0.0002517138,0.0002332674],"domain_scores_gemma":[0.9887122,0.0008472285,0.0008451726,0.009505434,0.00007317858,0.0000167997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004628166,0.00008347165,0.0001578164,0.0003165918,0.0002058555,0.00006209908,0.003316559,6.015448e-7,0.000003489712,0.08801657,0.1699968,0.7377938],"study_design_scores_gemma":[0.0001705245,0.00002896731,0.00005199707,0.0002829091,0.00002607584,0.000006426533,0.00007015413,0.000859014,0.000005474848,0.1104365,0.8878323,0.0002296707],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001991023,0.08441095,0.6486274,0.03008535,0.01507003,0.01118267,0.01090719,0.001012952,0.1986835],"genre_scores_gemma":[0.009820799,0.1010659,0.8483828,0.002728995,0.005812156,0.0009737106,0.01204461,0.000153159,0.01901794],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7375641,"threshold_uncertainty_score":0.9921089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4472727736232271,"score_gpt":0.4476064309102067,"score_spread":0.0003336572869796495,"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."}}