{"id":"W2167459423","doi":"10.1093/mnras/stw005","title":"Cosmology and astrophysics from relaxed galaxy clusters – IV. Robustly calibrating hydrostatic masses with weak lensing","year":2016,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency; Smithsonian Astrophysical Observatory; Jet Propulsion Laboratory; Office of Science; Centre National de la Recherche Scientifique; Bundesministerium für Wirtschaft und Technologie; National Research Foundation; Space Telescope Science Institute; Smithsonian Institution; Alfred P. Sloan Foundation; National Astronomical Observatory of Japan; Danmarks Grundforskningsfond; U.S. Department of Energy; California Institute of Technology; National Aeronautics and Space Administration; National Science Foundation","keywords":"Physics; Astrophysics; Cosmology; Weak gravitational lensing; Hydrostatic equilibrium; Redshift; Galaxy cluster; Galaxy; Gravitational lens; RADIUS; Gravitational lensing formalism; 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":[0.00197905,0.0007124993,0.0004280846,0.001855083,0.0003995655,0.001933969,0.0008791085,0.0003751147,0.001517326],"category_scores_gemma":[0.007021444,0.0003174791,0.0004608154,0.001632912,0.0008541966,0.001346698,0.002686888,0.0008012983,0.0006620715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005214941,"about_ca_system_score_gemma":0.0003440782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005314378,"about_ca_topic_score_gemma":0.005106025,"domain_scores_codex":[0.9990813,0.0001987937,0.00006638554,0.0002579143,0.0003083817,0.00008732992],"domain_scores_gemma":[0.9957593,0.0005143899,0.001547003,0.001433299,0.0004342595,0.0003118317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003244231,0.00004393835,0.8358482,0.0003751889,0.0009100859,0.0002200986,0.0006799205,0.00953118,0.03776996,0.01064901,0.003368188,0.1002797],"study_design_scores_gemma":[0.00002083072,0.0001209871,0.9515898,0.00009229229,0.0001229871,0.0003913655,0.0002914434,0.01331268,0.01197413,0.01011427,0.0118868,0.00008247513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9408481,0.003497823,0.04382137,0.0007501991,0.0001234528,0.00005223354,0.001528949,0.0004300136,0.008947803],"genre_scores_gemma":[0.9801466,0.0005434589,0.01583664,0.0001850075,0.0001225588,0.00002262432,0.001994356,0.0001234398,0.001025287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005314378,"threshold_uncertainty_score":0.01056689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006088022716743007,"score_gpt":0.1788113913485408,"score_spread":0.1727233686317978,"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."}}