{"id":"W4394975215","doi":"10.1093/mnras/stae1018","title":"DanceCam: atmospheric turbulence mitigation in wide-field astronomical images with short-exposure video streams","year":2024,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics; University of Victoria","funders":"H2020 European Research Council; Agence Nationale de la Recherche; European Commission","keywords":"Physics; Stars; Turbulence; Speckle imaging; Noise (video); Angular resolution (graph drawing); Speckle pattern; Field (mathematics); Remote sensing; Astrophysics; Image (mathematics); Optics; Artificial intelligence; Meteorology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001620674,0.0002848281,0.0003437237,0.000007732819,0.000109436,0.0001193217,0.0003197757,0.00008277666,0.00007090164],"category_scores_gemma":[0.000007445211,0.0002035534,0.0003467642,0.0001393989,0.0002363125,0.0002122918,0.0001696235,0.0004729221,0.000007337534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001149208,"about_ca_system_score_gemma":0.00009545647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005259674,"about_ca_topic_score_gemma":0.00002918974,"domain_scores_codex":[0.9984701,0.00005459762,0.000410068,0.0004580302,0.0001996706,0.0004074932],"domain_scores_gemma":[0.9991772,0.0002686858,0.0001128516,0.0003066806,0.00004052771,0.00009401974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004093542,0.00007700887,0.3473976,0.00001760779,0.0001207511,2.921776e-7,0.0001960202,0.646778,0.00004810724,0.0001505929,0.0004446352,0.00472842],"study_design_scores_gemma":[0.0003592822,0.0001659051,0.2240795,0.0002628665,0.0000967519,1.344001e-8,0.0008904871,0.7713894,0.002040208,0.0001019211,0.0003387768,0.0002749118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931638,0.0001765316,0.004736275,0.0007372978,0.0001794192,0.0002629427,0.0000635144,0.00002712724,0.0006531515],"genre_scores_gemma":[0.9814557,1.497491e-7,0.01805526,0.00002134515,0.0002402874,0.00001372003,0.0000218664,0.00003270118,0.0001590006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1246113,"threshold_uncertainty_score":0.8300669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004865952151880284,"score_gpt":0.2024471657706711,"score_spread":0.1975812136187908,"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."}}