{"id":"W2158454843","doi":"10.1088/0067-0049/197/2/36","title":"CANDELS: THE COSMIC ASSEMBLY NEAR-INFRARED DEEP EXTRAGALACTIC LEGACY SURVEY—THE <i>HUBBLE SPACE TELESCOPE</i> OBSERVATIONS, IMAGING DATA PRODUCTS, AND MOSAICS","year":2011,"lang":"en","type":"article","venue":"The Astrophysical Journal Supplement Series","topic":"Galaxies: Formation, Evolution, Phenomena","field":"Physics and Astronomy","cited_by":2070,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dominion Astrophysical Observatory","funders":"Science and Technology Facilities Council; Space Telescope Science Institute; National Aeronautics and Space Administration","keywords":"Physics; Wide Field Camera 3; Galaxy; Hubble space telescope; Advanced Camera for Surveys; Hubble Ultra-Deep Field; Astronomy; Data reduction; COSMIC cancer database; Sky; Remote sensing; Observational astronomy; Photometry (optics); Astrophysics; Telescope; Computer science; Geography; Hubble Deep Field; Stars","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":[0.001385029,0.0007788248,0.0005635408,0.004205084,0.0005419754,0.001425158,0.001122792,0.0002759413,0.009436022],"category_scores_gemma":[0.002274073,0.0004499197,0.0005713263,0.004483519,0.0001862622,0.001007912,0.001592636,0.0007946562,0.008018985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000782919,"about_ca_system_score_gemma":0.002253365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04436667,"about_ca_topic_score_gemma":0.05132274,"domain_scores_codex":[0.9990547,0.00007005148,0.00005774865,0.0002087772,0.0004624196,0.0001462403],"domain_scores_gemma":[0.9977815,0.00006976485,0.0004871624,0.0006202025,0.000636132,0.0004052426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005437395,0.000218313,0.2369671,0.0003610925,0.0003171845,0.0002544995,0.0003589323,0.001833878,0.009912983,0.004527023,0.4680858,0.2766196],"study_design_scores_gemma":[0.00009067328,0.00006607029,0.5234452,0.00009975812,0.00006935321,0.0001915518,0.00012609,0.001752157,0.004702404,0.00109904,0.4682959,0.00006178653],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1036224,0.001031336,0.02816212,0.0003949295,0.0001912669,0.001066381,0.81197,0.01352839,0.04003317],"genre_scores_gemma":[0.04210251,0.0003787436,0.0362439,0.0002267292,0.000122273,0.0004515952,0.9098144,0.001249906,0.009410011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04436667,"threshold_uncertainty_score":0.08821684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03598495177352908,"score_gpt":0.2365517451620096,"score_spread":0.2005667933884805,"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."}}