{"id":"W4281656139","doi":"10.5194/amt-15-3439-2022","title":"Ground-based validation of the MetOp-A and MetOp-B GOME-2 OClO measurements","year":2022,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Eurostars; Canadian Space Agency; Max-Planck-Institut für Chemie; Serono Symposia International Foundation; European Organization for the Exploitation of Meteorological Satellites; Ministerio de Ciencia e Innovación; University of Leeds; Environment and Climate Change Canada; Belgian Federal Science Policy Office","keywords":"Differential optical absorption spectroscopy; Satellite; Environmental science; Zenith; Remote sensing; Atmospheric sciences; Meteorology; SCIAMACHY; Ozone; Troposphere; Absorption (acoustics); Physics; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001461326,0.0008881895,0.0003399583,0.001450473,0.0005414939,0.0007545534,0.0007782684,0.0007285227,0.001189159],"category_scores_gemma":[0.002194041,0.0002061764,0.0004778889,0.001521897,0.0003227724,0.0007775397,0.0009836387,0.0003757147,0.0007830383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00064362,"about_ca_system_score_gemma":0.0007708743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02655833,"about_ca_topic_score_gemma":0.04258367,"domain_scores_codex":[0.9988531,0.0001564717,0.00006342904,0.0003555382,0.0004379307,0.0001335309],"domain_scores_gemma":[0.9983102,0.000194938,0.0003216367,0.0004475677,0.0006215219,0.0001040141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001674508,0.0007474798,0.6448472,0.0006178755,0.0007218941,0.0003875556,0.0005538728,0.04106418,0.2101753,0.0006318582,0.01022626,0.08835201],"study_design_scores_gemma":[0.000204686,0.0002389355,0.8991901,0.00008619389,0.0001502308,0.0001094588,0.0002387899,0.03696896,0.04869225,0.0001877434,0.0138628,0.00006994875],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580375,0.0002944615,0.008223882,0.00007744961,0.0000777491,0.0001567538,0.02590327,0.0008980075,0.006330978],"genre_scores_gemma":[0.9378123,0.00009866869,0.01298809,0.0001269994,0.00003510094,0.0002677579,0.04723911,0.0002551363,0.00117692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02655833,"threshold_uncertainty_score":0.05280751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03841694379548791,"score_gpt":0.2242337352097945,"score_spread":0.1858167914143066,"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."}}