{"id":"W2998180866","doi":"10.1109/iccad45719.2019.8942176","title":"Strengthening PUFs using Composition","year":2019,"lang":"en","type":"article","venue":"","topic":"Physical Unclonable Functions (PUFs) and Hardware Security","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Arbiter; Computer science; Composition (language); Layer (electronics); Theoretical computer science; Resilience (materials science); Work (physics); Engineering; Parallel computing; Linguistics","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":[0.004673162,0.001593659,0.001137296,0.001328945,0.002233489,0.002174235,0.002020635,0.001938335,0.0108334],"category_scores_gemma":[0.01715607,0.001010491,0.00218265,0.0007578528,0.005565336,0.007723897,0.0101599,0.004334275,0.002505755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001180935,"about_ca_system_score_gemma":0.001459044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004779325,"about_ca_topic_score_gemma":0.0003859464,"domain_scores_codex":[0.9939212,0.001611552,0.0003423962,0.001206374,0.002081724,0.0008367794],"domain_scores_gemma":[0.987483,0.004862789,0.0009524752,0.00518668,0.00113166,0.0003835044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005205559,0.0001431765,0.002866021,0.0004722975,0.000187527,0.0008517625,0.0009328492,0.05982108,0.06768273,0.7519587,0.002870131,0.1116932],"study_design_scores_gemma":[0.0001011534,0.0007825105,0.001304019,0.0002450514,0.0003083633,0.001925699,0.0002925858,0.2794331,0.1316225,0.5353822,0.0484181,0.0001847141],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04028429,0.0002116337,0.9398572,0.0006958551,0.0001602698,0.0001553995,0.00007371466,0.001627756,0.01693388],"genre_scores_gemma":[0.7534816,0.0003167997,0.2335661,0.0005777996,0.0001907116,0.0002801673,0.0001205666,0.0004502417,0.01101617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0108334,"threshold_uncertainty_score":0.03624135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309271318733242,"score_gpt":0.2293495055348272,"score_spread":0.2162567923474948,"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."}}