{"id":"W7054611434","doi":"","title":"An ALMA survey of submillimetre galaxies in the Extended Chandra Deep Field South: high-resolution 870 mu m source counts","year":2013,"lang":"en","type":"article","venue":"Chalmers Publication Library (Chalmers University of Technology)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Natural Sciences; Science and Technology Facilities Council; Natural Sciences and Engineering Research Council of Canada; National Astronomical Observatory of Japan; European Southern Observatory; McGill University; National Science Council; L'Oreal USA; National Radio Astronomy Observatory; Vetenskapsrådet; National Science Foundation","keywords":"Millimeter; Galaxy; Submillimeter Array; Chandra Deep Field South; Bolometer; Source counts; Angular resolution (graph drawing); Hubble Deep Field; Field of view; Star formation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001205027,0.0001166014,0.0001623593,0.00053356,0.00007220353,0.00001758155,0.0006336049,0.0002139264,0.0004450302],"category_scores_gemma":[0.00002610891,0.0001174209,0.00003939148,0.001178364,0.0001926153,0.0006659194,0.00004986727,0.0001784614,0.00005366756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002016634,"about_ca_system_score_gemma":0.0000239632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002544386,"about_ca_topic_score_gemma":0.00001536413,"domain_scores_codex":[0.9992951,0.00004840163,0.0001708935,0.000185677,0.000121899,0.0001779872],"domain_scores_gemma":[0.9992312,0.00005749025,0.000104846,0.0004768468,0.00008613282,0.00004351877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002416648,0.001969302,0.443831,0.0007096581,0.0008069068,0.00001529196,0.01193075,0.002576231,0.01631899,0.1219752,0.2195791,0.180046],"study_design_scores_gemma":[0.001764265,0.0003721155,0.8813266,0.00007654703,0.00007939972,0.00001340344,0.01386836,0.0618494,0.01721425,0.002926084,0.01957588,0.0009337439],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964534,0.0006139895,0.01499925,0.007844487,0.0001323165,0.0009357774,0.0001222789,0.0009117576,0.009906172],"genre_scores_gemma":[0.9983283,0.0001536056,0.0008758803,0.00003213906,0.000008265726,0.000006658088,0.0001964197,0.00001542582,0.0003832647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4374956,"threshold_uncertainty_score":0.4872769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009114695822619034,"score_gpt":0.1749497832782829,"score_spread":0.1658350874556638,"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."}}