{"id":"W6921693320","doi":"10.1051/0004-6361/201527670/pdf","title":"CLASH-VLT: A highly precise strong lensing model of the galaxy cluster RXC J2248.7","year":2016,"lang":"en","type":"article","venue":"Springer Link (Chiba Institute of Technology)","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Financiadora de Estudos e Projetos; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Ministério da Ciência, Tecnologia e Inovação; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Deutsche Forschungsgemeinschaft; Space Telescope Science Institute; Division of Chemistry; Villum Fonden; Canadian Institute for Advanced Research; National Aeronautics and Space Administration","keywords":"Galaxy; Redshift; Mass distribution; Cosmology; Galaxy cluster; Cluster (spacecraft); Markov chain Monte Carlo; Weak gravitational lensing; Lens (geology); Photometric redshift; Halo","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":[0.001002329,0.0008210803,0.0007969896,0.000764075,0.0006042367,0.001153658,0.001886302,0.0007384166,0.001530951],"category_scores_gemma":[0.00272104,0.0006596888,0.0009815861,0.0005589304,0.001007972,0.0009574695,0.001055326,0.0007125869,0.0003160127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001657487,"about_ca_system_score_gemma":0.001326464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04879791,"about_ca_topic_score_gemma":0.03480013,"domain_scores_codex":[0.9996871,0.0001074249,0.00001198555,0.00008597784,0.00005504896,0.00005244655],"domain_scores_gemma":[0.9990416,0.0003306064,0.0002984436,0.0001196015,0.00009041266,0.0001192926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001511321,0.00003082796,0.00808317,0.00002922055,0.00006954055,0.00008389272,0.00004967673,0.9776675,0.001343403,0.01017461,0.000429315,0.001887758],"study_design_scores_gemma":[0.00004642216,0.00003374017,0.003428458,0.000003362445,0.00001315679,0.00002563485,0.00001436208,0.9922219,0.0001990037,0.003737276,0.0002633765,0.0000132723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9168763,0.0003603401,0.07520936,0.0003638502,0.0000158,0.00009160658,0.002164028,0.0003183674,0.004600327],"genre_scores_gemma":[0.9770489,0.0002042576,0.01749602,0.00006742533,0.00003546718,0.0001003197,0.002329892,0.00008285955,0.002634891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04879791,"threshold_uncertainty_score":0.09702772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01189350009603536,"score_gpt":0.210710158389805,"score_spread":0.1988166582937696,"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."}}