{"id":"W4226465153","doi":"10.1051/0004-6361/202142083","title":"KiDS-1000: Cosmic shear with enhanced redshift calibration","year":2022,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Spanish National Plan for Scientific and Technical Research and Innovation; Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas; Science and Technology Facilities Council; Deutsche Forschungsgemeinschaft; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; National Natural Science Foundation of China; Institut de Física d'Altes Energies; Alexander von Humboldt-Stiftung","keywords":"Physics; Astrophysics; Redshift; COSMIC cancer database; Astronomy; Calibration; Shear (geology); Galaxy","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":[0.001681491,0.000824047,0.0005595757,0.004644156,0.0002834955,0.001068486,0.0008030468,0.0003032245,0.003270243],"category_scores_gemma":[0.00457261,0.0004198253,0.0008344233,0.003606741,0.0002304676,0.0007096992,0.001332755,0.0007803637,0.001572884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004822479,"about_ca_system_score_gemma":0.0003711549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00527891,"about_ca_topic_score_gemma":0.005594175,"domain_scores_codex":[0.9989157,0.0002065918,0.00007378871,0.0002768826,0.0003902723,0.0001368059],"domain_scores_gemma":[0.9978011,0.000318327,0.000420455,0.0008372806,0.0004764438,0.0001462587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001056314,0.0003430344,0.6020067,0.0003373943,0.001306564,0.0004790183,0.0005889066,0.07251425,0.02760272,0.01194992,0.04173825,0.2400769],"study_design_scores_gemma":[0.0002463069,0.0002172159,0.6147102,0.00006682065,0.0002113668,0.0006265853,0.0002404595,0.2592008,0.03536842,0.007908436,0.08094145,0.0002619267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7441592,0.000298142,0.1747185,0.0001742477,0.0001975888,0.0002139244,0.04988331,0.02054202,0.00981305],"genre_scores_gemma":[0.7638059,0.0001085833,0.1577282,0.00006737817,0.0001223629,0.0001834249,0.07357062,0.002218693,0.002194833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00527891,"threshold_uncertainty_score":0.01094002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004155006937418983,"score_gpt":0.1808726208398761,"score_spread":0.1767176139024571,"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."}}