{"id":"W2245387497","doi":"10.1051/0004-6361/201527746","title":"Measures of galaxy dust and gas mass with<i>Herschel</i>photometry and prospects for ALMA","year":2015,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Astronomical Observatories, Chinese Academy of Sciences; Science and Technology Facilities Council; Max-Planck-Institut für Astronomie; Centre National de la Recherche Scientifique; KU Leuven; Università degli Studi di Padova; Bundesministerium für Verkehr, Innovation und Technologie; Centre National d’Etudes Spatiales; Cardiff University; University of Sussex; National Aeronautics and Space Administration; California Institute of Technology; University of Lethbridge; Imperial College London; UK Space Agency","keywords":"Black-body radiation; Galaxy; Redshift; Spectral energy distribution; Wavelength; Star formation; Scaling; Cosmic dust; Monte Carlo method","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":[0.008386816,0.0008009563,0.000436262,0.002392109,0.0004060711,0.002981763,0.001898304,0.001224187,0.001932535],"category_scores_gemma":[0.02340873,0.0004474287,0.0007413158,0.001701696,0.0009906848,0.003470407,0.00196311,0.0007648895,0.0007555496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009105158,"about_ca_system_score_gemma":0.0002822729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004686776,"about_ca_topic_score_gemma":0.003873596,"domain_scores_codex":[0.9963541,0.00127951,0.0001587154,0.001181351,0.0007340004,0.0002922761],"domain_scores_gemma":[0.9767153,0.007713466,0.007258788,0.005445002,0.001773397,0.001093986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001907534,0.00005051142,0.967671,0.00005180072,0.0003670256,0.00006541509,0.0001908083,0.01085542,0.00177133,0.002632244,0.0007506864,0.01540294],"study_design_scores_gemma":[0.00001852153,0.0001791135,0.9085971,0.00009697473,0.0001377495,0.0002308778,0.0003165324,0.07439553,0.002966263,0.009328118,0.003641038,0.00009214637],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662446,0.001967294,0.01814301,0.001112738,0.00004636905,0.00004232052,0.002212555,0.0005437165,0.009687374],"genre_scores_gemma":[0.9940895,0.0001350172,0.003913491,0.0001151835,0.00005846023,0.00001022429,0.001087069,0.00004257768,0.0005486023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008386816,"threshold_uncertainty_score":0.04435426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253358303786353,"score_gpt":0.2035803033854555,"score_spread":0.1910467203475919,"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."}}