{"id":"W4392822442","doi":"10.48550/arxiv.2403.08241","title":"The 3D Lyman-$α$ Forest Power Spectrum from eBOSS DR16","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; University of Colorado Boulder; Office of Science; Max-Planck-Institut für Astronomie; Ministério da Ciência, Tecnologia e Inovação; University of Oxford; York University; Leibniz-Gemeinschaft; University of Notre Dame; Instituto de Astrofísica de Canarias; Simons Society of Fellows; Carnegie Mellon University; Universidad Nacional Autónoma de México; Alfred P. Sloan Foundation; University of Washington; Johns Hopkins University; Carnegie Institution of Washington; University of Utah; Ohio State University; U.S. Department of Energy; Smithsonian Institution; New Mexico State University; University of Portsmouth; Vanderbilt University; Yale University; Max-Planck-Institut für Astrophysik","keywords":"Alpha (finance); Lyman-alpha forest; Power (physics); Environmental science; Physics; Astronomy; Business; Intergalactic medium; Marketing","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":[0.0006497939,0.0005374103,0.0003808304,0.001146907,0.0002304669,0.0005668119,0.0004818733,0.0003469989,0.001136362],"category_scores_gemma":[0.001609253,0.0002743019,0.0006049572,0.0007886942,0.0002988036,0.0004403409,0.000706477,0.0003938877,0.0008795375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003950644,"about_ca_system_score_gemma":0.0002749088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008141861,"about_ca_topic_score_gemma":0.008309367,"domain_scores_codex":[0.9996892,0.00004439538,0.00001205498,0.00007733165,0.0001132548,0.0000638639],"domain_scores_gemma":[0.9993799,0.00008887615,0.0001173606,0.0001346434,0.0001343351,0.0001447993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008686586,0.0003267432,0.6167363,0.000273406,0.0005844124,0.001468941,0.0007641131,0.1637154,0.1043077,0.003787536,0.02483226,0.08233457],"study_design_scores_gemma":[0.000145372,0.000185283,0.6764106,0.00005727283,0.00008817143,0.0009022005,0.0002447665,0.283553,0.0191023,0.003316906,0.01584972,0.0001444379],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768029,0.0001636712,0.009994384,0.0001249865,0.00002628568,0.00002676555,0.008891636,0.001886988,0.002082309],"genre_scores_gemma":[0.9551433,0.00008803581,0.01461126,0.00007789363,0.00003852839,0.00002912861,0.02896854,0.0003663345,0.0006771096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008141861,"threshold_uncertainty_score":0.01618898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505767460542838,"score_gpt":0.1692439524281324,"score_spread":0.144186277822704,"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."}}