{"id":"W3212030079","doi":"","title":"Iron: Functional Encryption using Intel SGX","year":2016,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Guard (computer science); Cryptographic primitive; Cryptography; Encryption; Context (archaeology); Theoretical computer science; Functional encryption; Construct (python library); Cryptographic protocol; Computer security; Programming language; Ciphertext","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":[0.0005481455,0.0004287232,0.0004698755,0.0003934669,0.0003358927,0.0001696023,0.001716519,0.0004313045,0.0001759181],"category_scores_gemma":[0.0002477576,0.0004089835,0.0002845528,0.0001571388,0.0003733371,0.0002313469,0.004146776,0.001155632,0.0004309089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002287062,"about_ca_system_score_gemma":0.0004331807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002553137,"about_ca_topic_score_gemma":0.000007374972,"domain_scores_codex":[0.9965539,0.0004603808,0.000669151,0.001380289,0.0003750376,0.0005612379],"domain_scores_gemma":[0.9968308,0.0008157306,0.0005493065,0.001439206,0.0001953809,0.0001695815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000024249,0.00006825323,0.001360929,0.00005338403,0.00006200206,0.00001806216,0.001282423,0.002569875,0.002252909,0.9811967,0.0003748205,0.01073638],"study_design_scores_gemma":[0.0002842008,0.00002947863,0.005418396,0.0001705092,0.00001876717,0.0001102888,0.00003728906,0.1123153,0.0007744191,0.8783542,0.002024553,0.0004626068],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03699733,0.0001175224,0.9525559,0.001620665,0.004719831,0.0003419513,0.00001962554,0.0003882431,0.003238949],"genre_scores_gemma":[0.3204944,0.00004594445,0.6779408,0.0004302252,0.0009512287,0.00006604759,0.00003884578,0.0000278844,0.000004634087],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.283497,"threshold_uncertainty_score":0.9998362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05872375147886557,"score_gpt":0.2922273820116055,"score_spread":0.2335036305327399,"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."}}