{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001197929,0.0008813306,0.000642748,0.001598351,0.0003775242,0.00171584,0.001620724,0.001395217,0.001641742],"category_scores_gemma":[0.00376165,0.0003611772,0.001511627,0.001205403,0.0004899291,0.001266064,0.0009140165,0.001076585,0.001489139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001164908,"about_ca_system_score_gemma":0.001030228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01408446,"about_ca_topic_score_gemma":0.01279855,"domain_scores_codex":[0.9992219,0.000168204,0.00004654712,0.0002729367,0.000227222,0.00006311931],"domain_scores_gemma":[0.9984692,0.0003714648,0.0001985766,0.0004706304,0.0004196794,0.00007044333],"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":[0.0001956043,0.0001016659,0.01634868,0.0005556979,0.0002864055,0.000369647,0.0002470548,0.7655096,0.01985708,0.01183874,0.009109865,0.17558],"study_design_scores_gemma":[0.000009979814,0.00002603443,0.005855734,0.00002791148,0.00002767917,0.0003966063,0.00003166627,0.9732521,0.006116249,0.004720532,0.009512726,0.00002264518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04086434,0.001605503,0.9503111,0.0003145682,0.00007726828,0.0000919039,0.00209319,0.002065314,0.002576831],"genre_scores_gemma":[0.6192399,0.001472048,0.364579,0.0002546745,0.0001326428,0.0001466577,0.008168067,0.0004736256,0.005533434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01408446,"threshold_uncertainty_score":0.02800494,"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."}}