{"id":"W4401319384","doi":"10.48550/arxiv.2408.00922","title":"Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method","year":2024,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; University of Waterloo","funders":"SLAC National Accelerator Laboratory; Deutsche Forschungsgemeinschaft; High Energy Physics; Office of Science; Institut de Física d'Altes Energies; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Centres de Recerca de Catalunya; Argonne National Laboratory; European Regional Development Fund; U.S. Department of Energy; European Commission; Science and Technology Facilities Council; University College London; University of Portsmouth; Ohio State University; Integrated Electronics Engineering Center, Binghamton University; University of Illinois at Urbana-Champaign; Lawrence Berkeley National Laboratory; University of Pennsylvania; Financiadora de Estudos e Projetos; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; University of Sussex; Ministério da Ciência, Tecnologia e Inovação; Generalitat de Catalunya; Fermilab; National Science Foundation","keywords":"Redshift; Physics; Photometric redshift; Astrophysics; Weak gravitational lensing; Redshift survey; Dark energy; Galaxy; Characterization (materials science); Cosmology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004333853,0.0002220282,0.0001743447,0.00008515194,0.0002438149,0.0001842231,0.0001979402,0.00009496307,0.00002964496],"category_scores_gemma":[0.00002779562,0.0002251914,0.00007794592,0.0008076943,0.00003488089,0.0004386573,0.00006267415,0.0002481708,0.00002940284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003647082,"about_ca_system_score_gemma":0.0000301985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002304971,"about_ca_topic_score_gemma":0.00006719272,"domain_scores_codex":[0.9988432,0.0001741631,0.0001776662,0.0003971299,0.00007345972,0.0003343753],"domain_scores_gemma":[0.9993416,0.0002080131,0.00004148201,0.0002793421,0.00005741508,0.0000721366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005104928,0.00006884566,0.001887404,0.0003514152,0.0005815556,0.0001280088,0.001629351,0.0895563,0.8799262,0.01305042,0.006803853,0.005965597],"study_design_scores_gemma":[0.0003043219,0.00002104399,0.001227813,0.0002579747,0.0001880081,0.00002405542,0.0004989291,0.8041762,0.1524817,0.0003201149,0.03978219,0.0007177091],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3040412,0.0001810982,0.6936341,0.00004562409,0.0005941883,0.00007094482,0.00007288343,0.0008612133,0.0004987121],"genre_scores_gemma":[0.9981855,0.0001642258,0.0004277296,0.00003579613,0.00009195587,3.579092e-7,0.0004383262,0.00005672327,0.0005994198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7274445,"threshold_uncertainty_score":0.918304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767681085164182,"score_gpt":0.1674048781621946,"score_spread":0.1497280673105528,"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."}}