{"id":"W1963565113","doi":"10.1103/physrevd.91.043534","title":"Optimal estimator for resonance bispectra in the CMB","year":2015,"lang":"en","type":"article","venue":"Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D, Particles, fields, gravitation, and cosmology","topic":"Cosmology and Gravitation Theories","field":"Physics and Astronomy","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Centre National d’Etudes Spatiales; Agence Nationale de la Recherche; National Science Foundation","keywords":"Bispectrum; Multipole expansion; Physics; Cosmic microwave background; Estimator; Monodromy; Omega; Axion; Factorization; Spectral density; Particle physics; Quantum mechanics; Algorithm; Anisotropy; Mathematics; Statistics; Pure mathematics; Dark matter","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":[0.003155893,0.000790239,0.0006859837,0.00138954,0.0005357593,0.001614599,0.001663952,0.001375669,0.001990281],"category_scores_gemma":[0.01452124,0.0006739287,0.0005271921,0.0008405489,0.001321949,0.002213065,0.00127636,0.001616861,0.0008712462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008896807,"about_ca_system_score_gemma":0.0008280728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001212219,"about_ca_topic_score_gemma":0.001178103,"domain_scores_codex":[0.9988292,0.0004060792,0.00005044326,0.0002963711,0.0002899547,0.000127948],"domain_scores_gemma":[0.9969794,0.001644947,0.0003506242,0.0005527286,0.0003118112,0.0001605069],"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":[0.0008245377,0.0001926663,0.02296558,0.000352881,0.0002486322,0.0001974202,0.0002422288,0.4906706,0.04308906,0.2655901,0.004293835,0.1713326],"study_design_scores_gemma":[0.00003408548,0.00003301958,0.003519594,0.00004223591,0.00001892338,0.00008538359,0.00002809565,0.9158577,0.005400415,0.07319367,0.001727084,0.00005970384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04954113,0.0003509638,0.9473528,0.0003823486,0.00004460184,0.00002226139,0.000281874,0.0006152172,0.001408842],"genre_scores_gemma":[0.5002646,0.0004110794,0.4959005,0.0003702431,0.0001698269,0.0001101158,0.0009173581,0.0003371264,0.001519063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003155893,"threshold_uncertainty_score":0.01669014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02399113654093352,"score_gpt":0.3402217471377426,"score_spread":0.316230610596809,"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."}}