{"id":"W4404573502","doi":"10.1088/1475-7516/2025/07/018","title":"Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond","year":2025,"lang":"en","type":"article","venue":"Journal of Cosmology and Astroparticle Physics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; Perimeter Institute; University of Waterloo","funders":"Division of Astronomical Sciences; Science and Technology Facilities Council; High Energy Physics; U.S. Department of Energy; Gordon and Betty Moore Foundation; Agencia Estatal de Investigación; Office of Science; Ministerio de Ciencia, Innovación y Universidades; Commissariat à l'Énergie Atomique et aux Énergies Alternatives; National Science Foundation","keywords":"Systematics; Physics; Redshift; Astrophysics; Galaxy; Astronomy; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003111227,0.0001164239,0.0002628422,0.00004974737,0.0002163202,0.00005079883,0.00006704477,0.00001986374,0.000006101766],"category_scores_gemma":[0.00003117942,0.0001010773,0.00005994014,0.00009977471,0.0001086828,0.0002806355,0.00004202571,0.0001342429,6.910811e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000195531,"about_ca_system_score_gemma":0.00006574816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002589178,"about_ca_topic_score_gemma":1.709441e-7,"domain_scores_codex":[0.9991317,0.0000446772,0.0004573278,0.0000937763,0.00008258892,0.0001899348],"domain_scores_gemma":[0.9991086,0.0001725756,0.0003435052,0.00008047154,0.0002225674,0.00007229792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003300653,0.00005660279,0.9713065,0.0001141071,0.00007534332,4.544681e-8,0.0004056865,0.00007089868,0.002680355,0.02385053,0.0004044284,0.001002498],"study_design_scores_gemma":[0.001736082,0.0001958296,0.7134305,0.0002801612,0.0002277266,0.00002320484,0.00215362,0.02627034,0.01381096,0.2416648,0.00003881932,0.0001679489],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9581138,0.0002746911,0.04081921,0.0004341316,0.0001767153,0.0001223607,0.000004756672,0.000006055396,0.00004820903],"genre_scores_gemma":[0.9948666,0.000004148699,0.00479461,0.000007925737,0.0002131679,0.000007310251,0.00000281745,0.000007624136,0.00009580331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.257876,"threshold_uncertainty_score":0.4121812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008049208172646868,"score_gpt":0.246919268724563,"score_spread":0.2388700605519161,"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."}}