{"id":"W4384111567","doi":"10.1051/0004-6361/202347399","title":"CHEX-MATE: CLUster Multi-Probes in Three Dimensions (CLUMP-3D)","year":2024,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Astrophysics Division; Institut sur la Nutrition et les Aliments Fonctionnels; International Space Science Institute; Korea Advanced Institute of Science and Technology; Nuclear Safety and Security Commission; Centre National d’Etudes Spatiales; Science and Technology Facilities Council; California Institute of Technology; Academia Sinica; European Commission; National Science and Technology Council; National Aeronautics and Space Administration","keywords":"Physics; Astrophysics; Galaxy cluster; Structure formation; Cosmology; Cluster (spacecraft); Galaxy; Void (composites); Statistical physics; Astronomy","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":[0.0006941877,0.0005884058,0.0006304026,0.0007829533,0.0008670461,0.001457227,0.00172272,0.001096193,0.004696428],"category_scores_gemma":[0.002867917,0.0005445176,0.000866409,0.001068487,0.0006220986,0.001367836,0.003208474,0.001803699,0.001281024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005706942,"about_ca_system_score_gemma":0.0009813023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007081362,"about_ca_topic_score_gemma":0.009027038,"domain_scores_codex":[0.9996297,0.00008647625,0.000008963138,0.00009199837,0.0001167507,0.00006603463],"domain_scores_gemma":[0.9991371,0.000273291,0.0001205654,0.0002682933,0.00007226664,0.0001284844],"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":[0.002058027,0.0004448913,0.0886929,0.0007503705,0.0007132263,0.001398245,0.002489349,0.2405573,0.05845022,0.144758,0.2093528,0.2503347],"study_design_scores_gemma":[0.0001569651,0.0001011388,0.02279145,0.00004409629,0.00004300539,0.0002907077,0.0002699415,0.8635646,0.01119061,0.03763244,0.06377184,0.0001433367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2237449,0.000728264,0.6542901,0.001121618,0.000329102,0.0003861189,0.04043591,0.06710304,0.01186097],"genre_scores_gemma":[0.529941,0.0002703478,0.4355585,0.0005849368,0.0001067619,0.000790487,0.02601726,0.003789548,0.002941111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007081362,"threshold_uncertainty_score":0.01571113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008768381018160567,"score_gpt":0.2129378465139429,"score_spread":0.2041694654957824,"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."}}