{"id":"W1999947512","doi":"10.1002/qj.117","title":"Jacobian mapping between vertical coordinate systems in data assimilation","year":2007,"lang":"en","type":"article","venue":"Quarterly Journal of the Royal Meteorological Society","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Data assimilation; Jacobian matrix and determinant; Smoothing; Coordinate system; Interpolation (computer graphics); Numerical weather prediction; Cartesian coordinate system; Applied mathematics; Coordinate descent; Computer science; Mathematics; Linear interpolation; Algorithm; Remote sensing; Meteorology; Geometry; Mathematical analysis; Geology; Physics; Statistics","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":[0.004779341,0.0001631571,0.0004190014,0.00004883138,0.0002203351,0.00008405007,0.001007512,0.000228766,0.0003051201],"category_scores_gemma":[0.0002590926,0.00008813207,0.0002329523,0.0003737138,0.0001640843,0.0002379215,0.00004018375,0.0006906638,0.0000186443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002592058,"about_ca_system_score_gemma":0.00003311852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001509415,"about_ca_topic_score_gemma":0.00009486515,"domain_scores_codex":[0.9973932,0.0004618466,0.0009198554,0.000248624,0.0005123402,0.0004641245],"domain_scores_gemma":[0.9977941,0.001291257,0.0002788429,0.0003421513,0.00007739759,0.0002162859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001012791,0.00006036763,0.9377996,0.00001423399,0.00009843534,0.00002226304,0.0003814753,0.02358804,0.00007067934,0.000135121,0.0006851572,0.03704328],"study_design_scores_gemma":[0.0004734084,0.0004602713,0.9309473,0.00001971183,0.00004142444,0.000007545792,0.0004191596,0.06379652,0.000002592671,0.002233728,0.001478926,0.0001194363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860238,0.0005476722,0.01077692,0.0009693484,0.0005705265,0.0001791276,0.00003283504,0.00001538421,0.0008843793],"genre_scores_gemma":[0.9979289,0.000003830768,0.001362352,0.0002435563,0.0004044806,2.107102e-7,0.00001878029,0.00000305491,0.00003488735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04020847,"threshold_uncertainty_score":0.3593921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06110285038775699,"score_gpt":0.2661705049279796,"score_spread":0.2050676545402226,"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."}}