{"id":"W4394868965","doi":"10.1093/mnras/stae956","title":"The CluMPR galaxy cluster-finding algorithm and DESI legacy survey galaxy cluster catalogue","year":2024,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"SLAC National Accelerator Laboratory; High Energy Physics; Division of Astronomical Sciences; Science and Technology Facilities Council; Jet Propulsion Laboratory; Office of Science; University of Sussex; Ohio State University; Chinese Academy of Sciences; Alfred P. Sloan Foundation; Pennsylvania Space Grant Consortium; Université de Montréal; University of Portsmouth; U.S. Department of Energy; California Institute of Technology; National Aeronautics and Space Administration; National Science Foundation","keywords":"Physics; Astrophysics; Redshift; Galaxy cluster; Quasar; Cosmology; Galaxy; Photometric redshift; Astronomy; Dark matter; Cluster (spacecraft); Galaxy formation and evolution; Sky; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00126553,0.0007198763,0.0007417699,0.007080634,0.0007155137,0.001572445,0.00214577,0.0006066967,0.008066676],"category_scores_gemma":[0.00716483,0.000433138,0.00091005,0.003756374,0.0002392193,0.0009426455,0.001881504,0.0006327836,0.00508804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097065,"about_ca_system_score_gemma":0.001443545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01570669,"about_ca_topic_score_gemma":0.0207676,"domain_scores_codex":[0.9992833,0.00006718934,0.00006525506,0.0002465718,0.0002335076,0.0001042998],"domain_scores_gemma":[0.9982092,0.0003630457,0.0002105544,0.0004678813,0.0006115591,0.0001377815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006355075,0.0002229472,0.1089085,0.0004227402,0.0003888108,0.000364066,0.0003742035,0.048607,0.006970661,0.01021286,0.1843891,0.6385035],"study_design_scores_gemma":[0.0004147552,0.0001632664,0.06854965,0.000119593,0.0001258145,0.0006364522,0.000404243,0.8167881,0.01531335,0.01294548,0.08439701,0.0001423291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.3801271,0.0008044232,0.348635,0.0007364834,0.0001476373,0.001517268,0.1366735,0.1089178,0.02244079],"genre_scores_gemma":[0.263177,0.0001644185,0.5815299,0.0001881244,0.00005535311,0.0006481939,0.145018,0.002579947,0.006638958],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01570669,"threshold_uncertainty_score":0.03123051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009928278154177062,"score_gpt":0.2166452017736619,"score_spread":0.2067169236194848,"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."}}