{"id":"W4226049827","doi":"10.1093/mnras/stac3542","title":"Accelerating BAO scale fitting using Taylor series","year":2022,"lang":"en","type":"preprint","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Scientific Research and Discoveries","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"","keywords":"Dark energy; Physics; Redshift; Cosmology; Metric expansion of space; Series (stratigraphy); Scaling; Taylor series; Scale (ratio); Galaxy; Measure (data warehouse); Function (biology); Astrophysics; Mathematical analysis; Computer science; Mathematics; Quantum mechanics; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005885172,0.0003360877,0.0004959491,0.00002068822,0.0008339065,0.0004300564,0.001287773,0.00009812301,0.001657472],"category_scores_gemma":[0.00002764549,0.0002666679,0.001061755,0.0001221941,0.0004348139,0.0002085773,0.004635506,0.00102776,0.000004236863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001645064,"about_ca_system_score_gemma":0.0002778994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002273739,"about_ca_topic_score_gemma":0.00001826784,"domain_scores_codex":[0.9975247,0.0001714699,0.0005676436,0.0006166992,0.0005272632,0.0005921665],"domain_scores_gemma":[0.9983611,0.000133955,0.0005886615,0.0007065437,0.00007442151,0.0001353493],"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":[0.00002821618,0.00009239485,0.09805109,0.00006651776,0.000168082,5.232164e-8,0.0007071291,0.899235,0.00007796089,0.0000765185,0.0008720984,0.0006249568],"study_design_scores_gemma":[0.0003969681,0.0000405398,0.02111292,0.00009915456,0.0001321204,5.56255e-9,0.008858863,0.9640245,0.003503534,0.0004074098,0.0009660322,0.0004579657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942826,0.0000875089,0.000181543,0.0002423657,0.0008612605,0.0004267758,0.000698562,0.00002437465,0.003195013],"genre_scores_gemma":[0.9859118,3.597847e-8,0.0121103,0.00001264756,0.0006173543,0.00005498587,0.0001030986,0.00003364766,0.001156082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07693817,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695110983855719,"score_gpt":0.2674454544855838,"score_spread":0.2404943446470266,"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."}}