{"id":"W4319299777","doi":"10.1093/mnras/stad401","title":"All-sky modelling requirements for Bayesian 21 cm power spectrum estimation with <scp>bayeseor</scp>","year":2023,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Radio Astronomy Observations and Technology","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"McGill Space Institute; European Commission; McGill University; Rhode Island Space Grant Consortium; H2020 European Research Council; National Aeronautics and Space Administration; Brown University; National Science Foundation","keywords":"Physics; Sky; Spectral density; Bayesian probability; Astrophysics; Spectrum (functional analysis); Statistical physics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004849212,0.0008827548,0.001031495,0.0005370332,0.0009276863,0.001873321,0.004140109,0.001334949,0.01888214],"category_scores_gemma":[0.02595595,0.0009616109,0.001358943,0.0007088285,0.00119393,0.002618592,0.002399219,0.001982222,0.004683358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001651416,"about_ca_system_score_gemma":0.003425188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02900448,"about_ca_topic_score_gemma":0.03226435,"domain_scores_codex":[0.9979082,0.0007366345,0.000132416,0.0001796185,0.0008149793,0.0002281141],"domain_scores_gemma":[0.9900449,0.00531147,0.0005564147,0.001889079,0.001888498,0.0003096589],"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":[0.0006560775,0.0001885767,0.007315597,0.0001833251,0.0002098706,0.0003175431,0.0003087315,0.8110463,0.005905992,0.0586882,0.01277542,0.1024044],"study_design_scores_gemma":[0.00002268393,0.000009130503,0.0001528537,0.0000154047,0.00000499677,0.00002872146,0.00001260411,0.9911017,0.001532841,0.005236196,0.00186855,0.00001421849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02098072,0.000127985,0.9577183,0.0004872018,0.00005022879,0.0001160673,0.0004113304,0.01331573,0.006792308],"genre_scores_gemma":[0.2632031,0.0001473627,0.7253507,0.0005520468,0.00005116021,0.0002564154,0.001418111,0.004683282,0.004337791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02900448,"threshold_uncertainty_score":0.0631671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506110486387933,"score_gpt":0.228523338420829,"score_spread":0.2134622335569497,"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."}}