{"id":"W4408257234","doi":"10.1007/978-981-96-2440-9_28","title":"MAS: A Machine Learning Framework for Aerospace Systems","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Aerospace; Computer science; Artificial intelligence; Engineering; Aerospace engineering","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":[0.00009053239,0.0005118321,0.0005948326,0.000384366,0.00005442726,0.00007466947,0.0002537412,0.0008342391,0.000008902281],"category_scores_gemma":[0.000927185,0.0005643672,0.0001588119,0.0002521831,0.00001120169,0.00002559225,0.00003481269,0.00190158,0.00001346456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003157223,"about_ca_system_score_gemma":0.00003700874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000841289,"about_ca_topic_score_gemma":0.000009544804,"domain_scores_codex":[0.9985225,0.000004611869,0.0003921234,0.0003823024,0.0001695239,0.0005289405],"domain_scores_gemma":[0.9970891,0.002436487,0.00005208448,0.0002803179,0.0000443219,0.00009763587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003786206,0.000006034587,0.000003847867,0.0002891207,0.00007047706,0.000009415474,0.00001364215,0.8421307,0.000147546,0.1503918,0.0001193397,0.006814254],"study_design_scores_gemma":[0.0001538087,0.00003412132,0.000002276833,0.0006003918,0.00005487195,0.000005980608,1.344569e-7,0.8753987,0.0005371807,0.0107126,0.112001,0.0004988832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00002869685,0.00889717,0.9833497,0.0001324183,0.0004622991,0.000708624,0.00007901886,0.0006416775,0.005700424],"genre_scores_gemma":[0.7379151,0.01013094,0.2179417,0.0003371788,0.003406562,0.002773221,0.001172068,0.001733616,0.02458962],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.765408,"threshold_uncertainty_score":0.9996808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005617552274249932,"score_gpt":0.2018441000980939,"score_spread":0.196226547823844,"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."}}