{"id":"W4407825966","doi":"10.1109/tai.2025.3544590","title":"SecureLLAMA: Secure FPGAs Using LLAMA Large Language Models","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Artificial Intelligence","topic":"Physical Unclonable Functions (PUFs) and Hardware Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Field-programmable gate array; Computer science; Programming language; Parallel computing; Computer architecture; Embedded 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002868998,0.0003198028,0.0003089369,0.0003882003,0.0007183639,0.0002731147,0.0008661162,0.0001812035,0.0001360582],"category_scores_gemma":[0.00001381585,0.000325029,0.0002693079,0.001696525,0.0001032322,0.0007145158,0.00001771909,0.0006177414,0.0002563779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001670003,"about_ca_system_score_gemma":0.0002143216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001887768,"about_ca_topic_score_gemma":0.0003978228,"domain_scores_codex":[0.9976285,0.0001252514,0.0004831696,0.0007612754,0.000396708,0.0006051275],"domain_scores_gemma":[0.9984857,0.0001810012,0.00008364133,0.0008903624,0.0002013928,0.0001579309],"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":[0.00007841312,0.001285185,9.626223e-7,0.00005079519,0.0001035872,0.0000397004,0.003050988,0.3166329,0.006973706,0.5706066,0.0002849041,0.1008923],"study_design_scores_gemma":[0.00005846419,0.00007110884,0.000001408747,0.00006743617,0.00003400556,0.000006156249,0.000375906,0.7505199,0.1483992,0.09927572,0.0008981912,0.0002924763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01210579,0.0001172584,0.9815724,0.0005910237,0.002018096,0.0003013133,0.0000512668,0.0004155337,0.002827264],"genre_scores_gemma":[0.9931535,0.00003498177,0.005431891,0.0006336825,0.0001149692,0.00003287668,0.000002625853,0.00001848913,0.0005770084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9810477,"threshold_uncertainty_score":0.9999202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03582729545104406,"score_gpt":0.2982673236581781,"score_spread":0.262440028207134,"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."}}