{"id":"W4403023799","doi":"10.1109/bdai62182.2024.10692447","title":"Machine Learning for Polar Codes in Small IoT Devices","year":2024,"lang":"en","type":"article","venue":"","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Internet of Things; Polar; Computer security; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001799244,0.0000731687,0.00007162971,0.0000229616,0.00003352169,0.00003211437,0.00007839302,0.00008001185,0.00001590894],"category_scores_gemma":[0.00006116115,0.00005054225,0.00005279906,0.00005218628,0.00001471811,5.55564e-7,0.00006105656,0.0000711582,0.000005653562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003951262,"about_ca_system_score_gemma":0.00001283478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006356995,"about_ca_topic_score_gemma":0.0003505353,"domain_scores_codex":[0.9994961,0.00002575089,0.00009813669,0.0002118125,0.00001891202,0.0001492611],"domain_scores_gemma":[0.999868,0.00003341949,0.000010785,0.00005061447,0.00001333264,0.00002378486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006679194,0.00004598441,0.06233475,0.0001339056,0.00004972053,0.000009859679,0.00003117834,0.0003488146,0.8755113,0.002414848,0.0003447844,0.05870799],"study_design_scores_gemma":[0.0004825704,0.0009744201,0.006432754,0.00007827806,0.00001728651,0.00001559293,0.00009798224,0.0414521,0.1460054,0.0008286091,0.803186,0.0004289962],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844026,0.0050601,0.007331859,0.0002301702,0.00008516976,0.000103399,0.000007038384,0.00003911377,0.00274058],"genre_scores_gemma":[0.9956757,0.00004561521,0.002303606,0.0002515683,0.0001389668,0.000005889672,0.0001034235,0.00000743968,0.001467776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8028412,"threshold_uncertainty_score":0.2061053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02051383924998931,"score_gpt":0.2701058753806214,"score_spread":0.2495920361306321,"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."}}