{"id":"W3102475268","doi":"10.1051/0004-6361/202039584","title":"Multi-CCD modelling of the point spread function","year":2020,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"Canadian Space Agency; Centre National de la Recherche Scientifique","keywords":"Point spread function; Cardinal point; Parametric statistics; Computer science; Context (archaeology); Galaxy; Parametric model; Image plane; Artificial intelligence; Physics; Computer vision; Algorithm; Optics; Astrophysics; Image (mathematics); Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002829748,0.0001528486,0.0001819335,0.00001006986,0.0001401697,0.00002594056,0.00009406995,0.00001938914,0.00002132246],"category_scores_gemma":[0.000001018086,0.0001205318,0.0001169765,0.00008328819,0.00008052795,0.0001331666,0.0001081333,0.0001679025,0.000006767936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000564475,"about_ca_system_score_gemma":0.00002546553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004663832,"about_ca_topic_score_gemma":2.845487e-7,"domain_scores_codex":[0.9993046,0.00002367644,0.0001875024,0.0002110134,0.00009209377,0.0001810943],"domain_scores_gemma":[0.9995577,0.00001718234,0.0001462906,0.0001491253,0.00004848545,0.00008126206],"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":[0.0002310992,0.0004866263,0.03219372,0.0000535283,0.0006123296,9.584866e-7,0.001961608,0.24098,0.03559527,0.1028971,0.0002579176,0.5847299],"study_design_scores_gemma":[0.005565967,0.0009793817,0.02106731,0.0002573684,0.0007099147,0.000001380226,0.01185052,0.8651299,0.04765709,0.006836765,0.03838932,0.001554996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1995169,0.00001504168,0.799578,0.000175763,0.00004966813,0.0001079859,0.00002432859,0.000008828257,0.0005234732],"genre_scores_gemma":[0.9217485,4.895896e-7,0.07787912,0.00004085192,0.0002677439,0.000001940992,0.00001038321,0.00001540377,0.00003552657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7222316,"threshold_uncertainty_score":0.4915142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02503887663741244,"score_gpt":0.2008861656828675,"score_spread":0.1758472890454551,"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."}}