{"id":"W2980870618","doi":"10.1017/s174392131700597x","title":"Metallicity distribution functions using Gaia-DR1 data","year":2017,"lang":"en","type":"article","venue":"Proceedings of the International Astronomical Union","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Leibniz-Gemeinschaft; Australian Research Council; Natural Sciences and Engineering Research Council of Canada; Australian Astronomical Optics-Macquarie; Deutsche Forschungsgemeinschaft; Javna Agencija za Raziskovalno Dejavnost RS; Macquarie University; European Commission; Johns Hopkins University; W. M. Keck Foundation; Agence Nationale de la Recherche; Leibniz-Institut für Astrophysik Potsdam; Australian National University; National Science Foundation; European Space Agency; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Metallicity; Milky Way; Galaxy; Stars; Skewness; Sample (material); Trigonometry; Distribution (mathematics); Astrophysics; Astronomy; Physics; Mathematics; Statistics; Geometry","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":[0.0005289413,0.0004030575,0.0003493913,0.005102475,0.0001917625,0.001019784,0.0004964515,0.0003343787,0.00392913],"category_scores_gemma":[0.002235985,0.000116782,0.0003783554,0.004064517,0.0001294907,0.000413195,0.0006300404,0.000328439,0.006912517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005556862,"about_ca_system_score_gemma":0.0002161558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01887676,"about_ca_topic_score_gemma":0.009494359,"domain_scores_codex":[0.9996552,0.00003321049,0.00002374271,0.0001286629,0.00008977675,0.00006939984],"domain_scores_gemma":[0.9983782,0.0001833551,0.0003950304,0.0003783174,0.0005361157,0.000129032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003116483,0.00005538699,0.916705,0.0001171462,0.000177591,0.0001925198,0.0003515264,0.01041227,0.008194789,0.001131005,0.0128794,0.04947169],"study_design_scores_gemma":[0.00001493807,0.00002523884,0.9754454,0.00001439173,0.00002164127,0.00009284155,0.0001230494,0.006974727,0.001594643,0.0002749042,0.01540002,0.00001824798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8602899,0.0001961302,0.002354922,0.00008050804,0.00001211533,0.00003554263,0.125884,0.001404508,0.009742361],"genre_scores_gemma":[0.8279247,0.00009875619,0.003164232,0.00002437822,0.00001574078,0.00002783295,0.1663536,0.0002861004,0.002104686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01887676,"threshold_uncertainty_score":0.03753376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0417777364891354,"score_gpt":0.2711741534802135,"score_spread":0.2293964169910781,"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."}}