{"id":"W2151294996","doi":"10.1086/526794","title":"MegaPipe: The MegaCam Image Stacking Pipeline at the Canadian Astronomical Data Centre","year":2008,"lang":"en","type":"article","venue":"Publications of the Astronomical Society of the Pacific","topic":"Astronomical Observations and Instrumentation","field":"Engineering","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"Herzberg Institute of Astrophysics","funders":"","keywords":"Pipeline (software); Calibration; Remote sensing; Computer science; Computer vision; Telescope; Image processing; Artificial intelligence; Environmental science; Image (mathematics); Geology; Physics; Optics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004367891,0.0001983737,0.0002109886,0.00002531747,0.001089,0.00007306916,0.002512282,0.00008703176,0.000176209],"category_scores_gemma":[0.00007812917,0.0001081593,0.0003523517,0.0003447215,0.0009691002,0.0003647241,0.0006930174,0.0004053618,0.00002729896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005463265,"about_ca_system_score_gemma":0.0002454924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002925081,"about_ca_topic_score_gemma":0.004628849,"domain_scores_codex":[0.9984295,0.00009908343,0.0005696196,0.000263838,0.000234712,0.0004032844],"domain_scores_gemma":[0.9972608,0.0001804324,0.0002485152,0.002088783,0.0001023739,0.0001190822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001680549,0.0001483828,0.4798628,0.00002799233,0.0004561919,5.035536e-9,0.001560863,0.08198102,0.004100357,0.002384255,0.4258369,0.003624479],"study_design_scores_gemma":[0.0004115691,0.000007409607,0.762464,0.00001771173,0.00009793917,0.00000157856,0.001405429,0.1596587,0.003449735,0.00007047093,0.07221384,0.0002016629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547864,0.00007977217,0.001821471,0.04113488,0.0002602227,0.0005700197,0.0006655696,0.00004089813,0.0006407977],"genre_scores_gemma":[0.9944832,0.00001013472,0.004383914,0.00004129019,0.000127186,0.00002607626,0.0002041531,0.00002975971,0.0006942629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.353623,"threshold_uncertainty_score":0.8375815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02674902574681252,"score_gpt":0.2140328607567562,"score_spread":0.1872838350099437,"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."}}