{"id":"W4403382363","doi":"10.1051/0004-6361/202450617","title":"<i>Euclid</i> preparation","year":2024,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University; Perimeter Institute; University of Waterloo","funders":"National Astronomical Observatory of Japan; Norsk Romsenter; Agenția Spațială Română; European Space Agency; Imperial College London; Agenzia Spaziale Italiana; Ministerio de Ciencia, Innovación y Universidades; Österreichische Forschungsförderungsgesellschaft; Fundação para a Ciência e a Tecnologia; Magyar Tudományos Akadémia; National Aeronautics and Space Administration; University of Oxford","keywords":"Physics; Markov chain Monte Carlo; Astrophysics; COSMIC cancer database; Monte Carlo method; Statistical physics; Weak gravitational lensing; Shear (geology); Markov chain; Sampling (signal processing); Astronomy; Galaxy; Redshift; Statistics; Optics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002758376,0.001332626,0.001322998,0.002025205,0.001142098,0.002519844,0.003385982,0.0008223527,0.3328418],"category_scores_gemma":[0.01777447,0.000828614,0.001333811,0.003115941,0.0007460674,0.001724222,0.00248467,0.001791837,0.1705449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001465452,"about_ca_system_score_gemma":0.001978623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006075788,"about_ca_topic_score_gemma":0.008521244,"domain_scores_codex":[0.9979725,0.0005227932,0.0001684265,0.0003787823,0.0007746498,0.0001827972],"domain_scores_gemma":[0.9892331,0.001558837,0.0003759009,0.004024689,0.004162621,0.0006447528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001970445,0.00001847861,0.0005575992,0.0002256289,0.0000282878,0.0002023406,0.0001265809,0.001421792,0.001944874,0.02222659,0.9364629,0.03658789],"study_design_scores_gemma":[0.00009587224,0.00003926151,0.001649952,0.0001137847,0.00001300412,0.0002790229,0.00005834871,0.00508264,0.004358076,0.01095606,0.9772971,0.00005689757],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.008978738,0.001240382,0.291338,0.005192749,0.01090516,0.001365173,0.4112487,0.04119831,0.2285327],"genre_scores_gemma":[0.06650884,0.001421942,0.2616343,0.002524148,0.002645865,0.002683928,0.4703387,0.04158442,0.1506578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3328418,"threshold_uncertainty_score":0.9516202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005150592993539277,"score_gpt":0.2084189199675547,"score_spread":0.2032683269740154,"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."}}