{"id":"W3098140820","doi":"10.1093/mnras/stab748","title":"Including beyond-linear halo bias in halo models","year":2021,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"H2020 European Research Council; Leibniz-Gemeinschaft; Horizon 2020 Framework Programme; Ministerio de Economía y Competitividad; Partnership for Advanced Computing in Europe AISBL; H2020 Marie Skłodowska-Curie Actions; Gauss Centre for Supercomputing; Leibniz-Rechenzentrum; European Commission","keywords":"Halo; Physics; Halo effect; Astrophysics; Dark matter; Galaxy; Spectral density; Halo mass function; Dark matter halo; Matter power spectrum; Galactic halo; Statistical physics; Statistics; Redshift; Mathematics","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":[0.001381071,0.0009241733,0.0006106895,0.0007618095,0.0004196765,0.0009555421,0.001966441,0.0007645856,0.002628997],"category_scores_gemma":[0.007621801,0.0003435719,0.0009664582,0.0005856826,0.0005451995,0.001335251,0.001340029,0.0009379779,0.0006702911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008283223,"about_ca_system_score_gemma":0.0009065541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008800537,"about_ca_topic_score_gemma":0.005674178,"domain_scores_codex":[0.9994507,0.0001970227,0.00001928417,0.00006544856,0.0001490997,0.0001184614],"domain_scores_gemma":[0.9980568,0.0007494121,0.0002084494,0.0004882044,0.0003283133,0.0001688696],"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":[0.00009573568,0.0000708633,0.01053923,0.0001006255,0.0001266133,0.0004428432,0.0001708047,0.9118018,0.005871727,0.05582548,0.001606146,0.0133482],"study_design_scores_gemma":[0.00001858773,0.000027539,0.002194622,0.00002059229,0.00002237633,0.0000883173,0.0000127189,0.9765661,0.001921569,0.01784734,0.001255517,0.00002472963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3173228,0.0008134173,0.647907,0.001235019,0.000296997,0.00013321,0.0005026227,0.003918387,0.02787058],"genre_scores_gemma":[0.9703559,0.0002613988,0.02435799,0.0003752877,0.00008448697,0.00006004242,0.0001692029,0.0007458791,0.003589828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008800537,"threshold_uncertainty_score":0.01749861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319627143509526,"score_gpt":0.2285755332203321,"score_spread":0.2053792617852369,"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."}}