{"id":"W4407710480","doi":"10.1093/mnras/staf285","title":"Neural network-based model of galaxy power spectrum: fast full-shape galaxy power spectrum analysis","year":2025,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Technology Facilities Council; Faculty of Arts and Sciences; Office of Science; Alliance de recherche numérique du Canada; SLAC National Accelerator Laboratory; Durham University; National Energy Research Scientific Computing Center; Conservation Federation of Missouri; Harvard University; High Energy Physics; U.S. Department of Energy","keywords":"Physics; Galaxy; Astrophysics; Spectral density; Interacting galaxy; Power (physics); Type-cD galaxy; Disc galaxy; Galaxy merger; Astronomy; Galaxy formation and evolution","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007861213,0.0004796381,0.0004942573,0.0004330152,0.0004084829,0.0005866648,0.001870931,0.001032973,0.004633532],"category_scores_gemma":[0.00304848,0.0004319186,0.0004999957,0.0003445573,0.0005867212,0.0007811263,0.0007192649,0.001166669,0.0007777669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001250134,"about_ca_system_score_gemma":0.0008986917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01759019,"about_ca_topic_score_gemma":0.01319291,"domain_scores_codex":[0.9998456,0.00005503932,0.000005336973,0.00002622555,0.00004365411,0.00002411154],"domain_scores_gemma":[0.9993326,0.0003538291,0.00005331455,0.00007148925,0.0001397034,0.00004888445],"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":[0.00002173315,0.00001170477,0.0007538906,0.000007341561,0.00001107293,0.0000218439,0.000009447505,0.9937043,0.000359066,0.001581098,0.0002340146,0.003284649],"study_design_scores_gemma":[0.000001554421,9.647922e-7,0.0000463847,6.673793e-7,4.204315e-7,0.000001680969,6.257627e-7,0.9994962,0.00007958797,0.0003421424,0.00002902703,6.999046e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2250494,0.0001827871,0.7630006,0.0006389819,0.00005460724,0.00007901669,0.0004189569,0.002446878,0.008128755],"genre_scores_gemma":[0.9038137,0.00005905005,0.09124795,0.0001930682,0.00003087374,0.0001352178,0.0004824929,0.0003022672,0.003735429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01759019,"threshold_uncertainty_score":0.03497559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007816696435529485,"score_gpt":0.2191314728716731,"score_spread":0.2113147764361436,"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."}}