{"id":"W2107744894","doi":"10.1051/0004-6361/200913334","title":"Non-parametric modeling of the intra-cluster gas using APEX-SZ bolometer imaging data","year":2010,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Astronomy and Astrophysical Research","field":"Physics and Astronomy","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Bundesministerium für Wirtschaft und Technologie; Bundesministerium für Bildung und Forschung; International Max Planck Research School for Advanced Methods in Process and Systems Engineering; European Southern Observatory; International Max Planck Research School for Environmental, Cellular and Molecular Microbiology; Deutsche Forschungsgemeinschaft; National Aeronautics and Space Administration; National Science Foundation","keywords":"Bolometer; Hydrostatic equilibrium; Observatory; Cluster (spacecraft); Entropy (arrow of time); RADIUS; Calibration; Spectroscopy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002383777,0.0003912082,0.0004416407,0.0001180519,0.0003891635,0.0001536585,0.001141181,0.00005119101,0.0001161289],"category_scores_gemma":[0.00001382483,0.0003094648,0.0002025961,0.0004916498,0.0003862723,0.0007454412,0.001347942,0.001016834,0.00001561255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001697455,"about_ca_system_score_gemma":0.0001914697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000274193,"about_ca_topic_score_gemma":0.000001919488,"domain_scores_codex":[0.9976702,0.00006320279,0.0004827446,0.0006811628,0.0003633271,0.0007393089],"domain_scores_gemma":[0.997966,0.0001080684,0.0002597343,0.001323573,0.0001251026,0.000217524],"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":[0.00007166571,0.0004247697,0.07500383,0.0000243768,0.0001899749,8.276525e-7,0.000133931,0.009340682,0.02690089,0.002462311,0.00009065545,0.8853561],"study_design_scores_gemma":[0.001992734,0.0001119992,0.004361834,0.0001171915,0.0002770376,0.000004182896,0.001116907,0.964931,0.02117092,0.002134374,0.002937137,0.0008446695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5318727,0.00000774302,0.4672392,0.00007899559,0.0001604964,0.0002190129,0.0001012967,0.000009596384,0.0003108927],"genre_scores_gemma":[0.9387626,5.100094e-7,0.06022369,0.0000190226,0.0008344044,0.00001287769,0.00006947693,0.00004349514,0.00003390404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9555903,"threshold_uncertainty_score":0.9999357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02071257863352699,"score_gpt":0.2731582439666116,"score_spread":0.2524456653330846,"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."}}