{"id":"W2591010855","doi":"10.1093/mnras/stx456","title":"The invisible AGN catalogue: a mid-infrared–radio selection method for optically faint active galactic nuclei","year":2017,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; University of California, Los Angeles; York University; Carnegie Mellon University; Office of Science; Johns Hopkins University; College of Engineering, Michigan State University; Harvard University; Ohio State University; New Mexico State University; University of Portsmouth; Yale University; Vanderbilt University; National Science Foundation; University of Washington; Alfred P. Sloan Foundation; Brookhaven National Laboratory; U.S. Department of Energy; California Institute of Technology; National Aeronautics and Space Administration; Jet Propulsion Laboratory; Princeton University","keywords":"Physics; Active galactic nucleus; Astrophysics; Galaxy; Supermassive black hole; Infrared; Astronomy; Population; Brightness","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":[0.001991185,0.0008680798,0.0009859758,0.01347868,0.00106476,0.00163692,0.001416994,0.0007497776,0.008129898],"category_scores_gemma":[0.004848326,0.0003698741,0.001258962,0.004856297,0.0003016833,0.000866307,0.001904181,0.0008128525,0.007848597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005063527,"about_ca_system_score_gemma":0.001680306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01091089,"about_ca_topic_score_gemma":0.01503354,"domain_scores_codex":[0.9986054,0.0001298011,0.0002004308,0.0002858264,0.0005750299,0.000203482],"domain_scores_gemma":[0.9967911,0.0004872519,0.0006020443,0.0006416084,0.001101942,0.0003760201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001080473,0.0006775795,0.2396143,0.0006973476,0.0005065557,0.001559566,0.001120168,0.003625091,0.04967411,0.003935337,0.1336032,0.5639063],"study_design_scores_gemma":[0.0004086535,0.0003615106,0.631879,0.0001963993,0.0004016758,0.002582058,0.0007033721,0.02849576,0.02352668,0.003056223,0.3080815,0.0003070498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4096339,0.002120903,0.3839179,0.0003600368,0.0004680657,0.004718245,0.1416912,0.02638984,0.03069993],"genre_scores_gemma":[0.2455197,0.0007861792,0.4733554,0.0003177216,0.0003169902,0.003275196,0.2552974,0.002563814,0.01856764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01347868,"threshold_uncertainty_score":0.02719718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009229673235870985,"score_gpt":0.2358497886585268,"score_spread":0.2266201154226558,"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."}}