{"id":"W4307466291","doi":"","title":"Introduction to signal processing and frenquency analysis with Fourier transforms","year":2019,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Fourier transform; SIGNAL (programming language); Signal processing; Computer science; Mathematics; Digital signal processing; Mathematical analysis; Computer hardware; Programming language","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":[0.003413987,0.0002965207,0.0004293059,0.0005777283,0.0002701082,0.0004732478,0.001234172,0.0002778419,0.00002726811],"category_scores_gemma":[0.0001429076,0.0002616688,0.0001153913,0.001193472,0.0001291048,0.0002846255,0.0002630588,0.0005183636,0.00001883338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009147864,"about_ca_system_score_gemma":0.0001999283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003077295,"about_ca_topic_score_gemma":0.0007801874,"domain_scores_codex":[0.996507,0.001181141,0.0003915209,0.001109938,0.0004927157,0.0003176687],"domain_scores_gemma":[0.9960229,0.0001562887,0.0003237633,0.001946168,0.00140739,0.0001434634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007820358,0.001096332,0.03653928,0.001169063,0.002033659,0.0000210204,0.05088085,0.00502692,0.02826859,0.1239271,0.002315916,0.7486431],"study_design_scores_gemma":[0.002718139,0.00001454524,0.0360974,0.005180368,0.001688181,0.0001494866,0.0007135817,0.4634316,0.4271975,0.01018698,0.04877966,0.003842568],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06132734,0.0004733626,0.9130918,0.02070907,0.0001212043,0.0006005861,0.000007011369,0.0003358421,0.003333746],"genre_scores_gemma":[0.8848794,0.00005518696,0.1124237,0.00008142587,0.00004369238,0.00008220021,0.00005498237,0.00002038142,0.002359064],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8235521,"threshold_uncertainty_score":0.9999835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225982517115235,"score_gpt":0.2140433313189427,"score_spread":0.2017835061477904,"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."}}