{"id":"W2144910248","doi":"10.1051/0004-6361/201118698","title":"HerMES: deep number counts at 250 <i>μ</i>m, 350 <i>μ</i>m and 500 <i>μ</i>m in the COSMOS and GOODS-N fields and the build-up of the cosmic infrared background","year":2012,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":229,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge; University of British Columbia","funders":"Science and Technology Facilities Council; Centre National de la Recherche Scientifique; National Aeronautics and Space Administration; California Institute of Technology; Imperial College London; National Astronomical Observatories, Chinese Academy of Sciences; UK Space Agency; Centre National d’Etudes Spatiales","keywords":"Spire (mollusc); Redshift; Physics; Astrophysics; Galaxy; Source counts; COSMIC cancer database; Astronomy; Population; Confusion; Cosmic infrared background; Flux (metallurgy); Cosmic microwave background; 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":[],"consensus_categories":[],"category_scores_codex":[0.001370439,0.0006245932,0.0003554388,0.00326552,0.0002838877,0.0007212713,0.000631864,0.0004134353,0.007671201],"category_scores_gemma":[0.001338166,0.0003193433,0.0003571652,0.001548429,0.00030316,0.001031959,0.001551577,0.0005435346,0.002653508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003519694,"about_ca_system_score_gemma":0.0003408375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003967773,"about_ca_topic_score_gemma":0.009292297,"domain_scores_codex":[0.9994808,0.00006047553,0.00002369604,0.0001526822,0.0001911579,0.00009124064],"domain_scores_gemma":[0.9986581,0.0001230295,0.000303012,0.0003199828,0.0002291363,0.0003667176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001280338,0.0003073432,0.5391833,0.0003331243,0.0003809218,0.0004683651,0.0009497437,0.004725795,0.03802421,0.02007225,0.2032316,0.191043],"study_design_scores_gemma":[0.0001090861,0.00008000166,0.8918808,0.00004564656,0.00006122532,0.0003442935,0.0001440149,0.007085355,0.01618891,0.005585126,0.07840317,0.00007237936],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5579652,0.001530459,0.05404959,0.0011008,0.0003544885,0.0002248846,0.303612,0.01195724,0.06920545],"genre_scores_gemma":[0.7322615,0.0003508582,0.0583983,0.0004567665,0.0003611256,0.0002098581,0.1882036,0.000694892,0.0190631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007671201,"threshold_uncertainty_score":0.02566272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006217205755650343,"score_gpt":0.2012167776450709,"score_spread":0.1949995718894205,"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."}}