{"id":"W4290728375","doi":"10.1051/0004-6361/201526075","title":"Hierarchical progressive surveys","year":2015,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Astrophysics Science Division; University of California, Los Angeles; Goddard Space Flight Center; Centre National de la Recherche Scientifique; National Aeronautics and Space Administration; California Institute of Technology; Jet Propulsion Laboratory","keywords":"Sky; Context (archaeology); Pixel; Visualization; Computer science; Tessellation (computer graphics); Data science; Angular resolution (graph drawing); Data visualization; Hierarchical database model; Data mining; Computer graphics (images); Remote sensing; Geography; Artificial intelligence; Archaeology; Meteorology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003611262,0.0005989453,0.0006814701,0.002473416,0.001280147,0.002605624,0.002318433,0.001104208,0.01764323],"category_scores_gemma":[0.01951903,0.0005132229,0.0004104487,0.007223994,0.001620353,0.003506225,0.003754156,0.00110929,0.005240169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001975082,"about_ca_system_score_gemma":0.003464829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.012279,"about_ca_topic_score_gemma":0.01521375,"domain_scores_codex":[0.994918,0.001763894,0.0002284307,0.001439319,0.001168118,0.000482227],"domain_scores_gemma":[0.9866959,0.005584201,0.001402177,0.00290762,0.002719462,0.0006906654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002108258,0.00009303316,0.02213216,0.001354167,0.00008600247,0.00028692,0.001030087,0.02904356,0.001420675,0.5441082,0.06502467,0.3352097],"study_design_scores_gemma":[0.0000861312,0.0001950391,0.01770788,0.0005415055,0.0001055168,0.001220887,0.001038275,0.05208645,0.001557075,0.3219766,0.6034142,0.00007040324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04059467,0.007464426,0.7979908,0.004234555,0.0005415613,0.0009019273,0.01771978,0.003144622,0.1274076],"genre_scores_gemma":[0.5070202,0.009721399,0.4263668,0.001534161,0.001029351,0.0009328881,0.01804898,0.0004180625,0.03492815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01764323,"threshold_uncertainty_score":0.05902255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117383405951924,"score_gpt":0.2194057553754002,"score_spread":0.208231921315881,"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."}}