{"id":"W4413883340","doi":"10.1088/1475-7516/2025/09/008","title":"DESI 2024 V: Full-Shape galaxy clustering from galaxies and quasars","year":2025,"lang":"en","type":"article","venue":"Journal of Cosmology and Astroparticle Physics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Perimeter Institute; University of Waterloo","funders":"Division of Astronomical Sciences; Science and Technology Facilities Council; Office of Science; Ministerio de Ciencia e Innovación; Gordon and Betty Moore Foundation; U.S. Department of Energy; Commissariat à l'Énergie Atomique et aux Énergies Alternatives; National Science Foundation","keywords":"Physics; Astrophysics; Quasar; Galaxy; Brightest cluster galaxy; Cluster analysis; Interacting galaxy; Astronomy; Lenticular galaxy; Galaxy cluster; Galaxy formation and evolution; Artificial intelligence","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":[0.001599883,0.0005950771,0.0005103219,0.001947352,0.0003632827,0.0009705631,0.001200946,0.0004906756,0.003378394],"category_scores_gemma":[0.002622552,0.0003810043,0.0006368394,0.001837712,0.000266829,0.0005060175,0.001573815,0.0003484386,0.00272866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007946051,"about_ca_system_score_gemma":0.0005513781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293473,"about_ca_topic_score_gemma":0.01957399,"domain_scores_codex":[0.9992579,0.0001215024,0.00002568336,0.0001808433,0.0003071485,0.0001069778],"domain_scores_gemma":[0.9984549,0.000174659,0.0002587136,0.0007111222,0.0002091663,0.0001914164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001201887,0.000281078,0.6372806,0.0003391923,0.0006244528,0.0004040415,0.0007230472,0.08713484,0.02469138,0.007492276,0.07265223,0.1671749],"study_design_scores_gemma":[0.0001157742,0.0002136967,0.8020463,0.00004927268,0.00005292412,0.0004035207,0.0002166508,0.1239623,0.0133724,0.004558523,0.05488899,0.0001196181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8353316,0.0003517875,0.02047075,0.0004035847,0.00006987661,0.0001241152,0.1160748,0.008639544,0.01853387],"genre_scores_gemma":[0.7969263,0.0000953471,0.02922769,0.0001361745,0.00007671211,0.0001089143,0.1690608,0.0007053352,0.003662745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01293473,"threshold_uncertainty_score":0.02571887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009633602168078004,"score_gpt":0.232914542674472,"score_spread":0.223280940506394,"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."}}