{"id":"W2951735440","doi":"10.48550/arxiv.1503.01147","title":"Random Pulse Train Spectrum Calculation Unleashed","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Train; Pulse (music); Spectral density; Blank; Spectrum (functional analysis); SIGNAL (programming language); Pulse wave; Power (physics); Cover (algebra); Mathematics; Statistical physics; Pulse duration; Mathematical analysis; Physics; Algorithm; Computer science; Telecommunications; Optics; Statistics; Engineering; Quantum mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004335428,0.0004726154,0.0005278825,0.0006405034,0.0003243867,0.0009362662,0.0007259553,0.0007357867,0.005700475],"category_scores_gemma":[0.002705297,0.0002499624,0.0005289009,0.0005513019,0.0007276811,0.001810576,0.0009311181,0.001346825,0.002236706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004335788,"about_ca_system_score_gemma":0.000610218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007329073,"about_ca_topic_score_gemma":0.0005568094,"domain_scores_codex":[0.999649,0.00006755156,0.00001726865,0.00005337555,0.0001962533,0.00001644307],"domain_scores_gemma":[0.99938,0.00025399,0.00002916966,0.0001481445,0.00016437,0.00002419918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007394099,0.00003327506,0.0005070432,0.000380631,0.00004880145,0.000291093,0.0001827148,0.1079337,0.02013321,0.6863822,0.00780831,0.1762251],"study_design_scores_gemma":[0.000008595771,0.00002558577,0.0002478892,0.00006745936,0.00001442559,0.0004482294,0.00003465157,0.7959603,0.009720988,0.1742717,0.01917358,0.00002653131],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00385578,0.0005341286,0.9865889,0.0002873762,0.0002181143,0.00001493038,0.00004270946,0.000357607,0.008100411],"genre_scores_gemma":[0.3900158,0.003234756,0.5569769,0.0005317452,0.0004886207,0.0001267554,0.000386778,0.001028414,0.04721028],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.005700475,"threshold_uncertainty_score":0.01906997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07752239289706081,"score_gpt":0.2104536105091986,"score_spread":0.1329312176121378,"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."}}