{"id":"W3103275108","doi":"10.1051/0004-6361/201527294","title":"The VIPERS Multi-Lambda Survey","year":2016,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Institut national des sciences de l'Univers; Centro de Estudos Ambientais e Marinhos, Universidade de Aveiro; Centre National de la Recherche Scientifique; Office of Science; Agence Nationale de la Recherche; National Aeronautics and Space Administration; California Institute of Technology; Alfred P. Sloan Foundation; Centre National d’Etudes Spatiales; U.S. Department of Energy; National Science Foundation","keywords":"Physics; Astrophysics; Cosmic variance; Galaxy; Redshift; Photometry (optics); Stellar mass; Photometric redshift; Sigma; Lambda; Star formation; COSMIC cancer database; Cosmic time; Diagram; Astronomy; Stars; Statistics","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":[0.0003773417,0.0001831742,0.0001659226,0.001216953,0.00023189,0.0002701166,0.0003674501,0.0001545283,0.002153846],"category_scores_gemma":[0.000400499,0.0001135265,0.0001382238,0.0009065161,0.0001037924,0.0002774757,0.0006242519,0.0002293208,0.0007064278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002678779,"about_ca_system_score_gemma":0.0001895252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01026908,"about_ca_topic_score_gemma":0.01568721,"domain_scores_codex":[0.9997833,0.00002630908,0.000006031758,0.00009154039,0.0000390917,0.00005369837],"domain_scores_gemma":[0.9995562,0.00004309044,0.000169571,0.00005455772,0.00003457422,0.0001419388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002059518,0.0000612818,0.9468819,0.00009299986,0.0001478376,0.0002505268,0.0005359915,0.001434531,0.00537295,0.0007605438,0.01212542,0.0321301],"study_design_scores_gemma":[0.000005904536,0.00003001953,0.9936057,0.000006404071,0.00000971077,0.0001267078,0.00008818444,0.0007949746,0.0002497786,0.00005800228,0.005018976,0.000005517033],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827203,0.0002204734,0.0004758761,0.00007075473,0.000005158133,0.00001610037,0.01387245,0.0001235645,0.002495438],"genre_scores_gemma":[0.9558831,0.000279905,0.003473948,0.000142247,0.00003865919,0.00005695288,0.03618403,0.00005879338,0.003882452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01026908,"threshold_uncertainty_score":0.02041858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003087686155552,"score_gpt":0.2049843985555151,"score_spread":0.1949535216939595,"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."}}