{"id":"W1601203605","doi":"10.1002/9780470171455.app3","title":"Appendix C: Primer on Linear Algebra","year":2007,"lang":"en","type":"other","venue":"","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; McMaster University","funders":"","keywords":"Cholesky decomposition; Orthogonalization; Mathematics; Linear algebra; Singular value decomposition; Factorization; QR decomposition; Eigenvalues and eigenvectors; Algebra over a field; Principal (computer security); Combinatorics; Computer science; Algorithm; Pure mathematics; Physics; Geometry","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002477356,0.0002242038,0.0002006475,0.0003585009,0.00003233138,0.00004629368,0.0009937936,0.0002236874,0.01482434],"category_scores_gemma":[0.000007614307,0.0001730015,0.00008473541,0.0002334942,0.00003103138,0.00004540436,0.0001703323,0.0002135026,0.02562045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001186541,"about_ca_system_score_gemma":0.00003020034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000264609,"about_ca_topic_score_gemma":0.00000281292,"domain_scores_codex":[0.9988537,0.00003494589,0.0001368789,0.0004324552,0.0002705306,0.0002714323],"domain_scores_gemma":[0.998965,0.00004793537,0.00008816023,0.0007927442,0.00001019018,0.00009598108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001279876,0.00003176743,7.127135e-7,0.00001016202,0.0000157807,0.00002312531,0.00001064321,5.309529e-7,0.00000150673,0.4975682,0.4745108,0.02782553],"study_design_scores_gemma":[0.0001141871,0.00004564075,9.848101e-7,0.00004529661,0.000003191927,0.000006213275,0.000001214449,0.0006587085,0.0004887157,0.002108294,0.9962822,0.0002453456],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[3.112204e-7,0.0001004302,0.3387558,0.00007867302,0.0005529135,0.0001063946,0.000002494902,0.000496918,0.6599061],"genre_scores_gemma":[0.000008835426,0.00001722014,0.07181115,0.0009755027,0.0006585476,0.000002635118,0.00000926563,0.000120437,0.9263964],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5217714,"threshold_uncertainty_score":0.9860762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272937112811983,"score_gpt":0.2607577688163786,"score_spread":0.2480283976882588,"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."}}