{"id":"W4210898914","doi":"10.5194/amt-15-701-2022","title":"Analysis of improvements in MOPITT observational coverage over Canada","year":2022,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Space Agency","keywords":"Environmental science; Troposphere; Moderate-resolution imaging spectroradiometer; Cloud computing; Satellite; Meteorology; Climatology; Remote sensing; Atmospheric sciences; Spectroradiometer; Geography; Computer science; Geology","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":[0.0005589193,0.0003118448,0.0002463216,0.001414474,0.000691194,0.0008444327,0.0005443307,0.0001774825,0.0007258336],"category_scores_gemma":[0.002303649,0.000136069,0.0003885238,0.003402384,0.0002076145,0.0003271349,0.0004316122,0.0002761837,0.0001395118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007584681,"about_ca_system_score_gemma":0.005137476,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9653118,"about_ca_topic_score_gemma":0.9750231,"domain_scores_codex":[0.9991555,0.00003496988,0.00003867119,0.0001858843,0.0004317675,0.0001531136],"domain_scores_gemma":[0.996936,0.0001803961,0.0002318155,0.0001452091,0.00237447,0.0001320753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003751011,0.00003810373,0.9428464,0.0001217428,0.0003065,0.00028709,0.000404036,0.006515082,0.009687633,0.0002834919,0.005905467,0.0332293],"study_design_scores_gemma":[0.000004172244,0.000006963086,0.9920805,0.00001170073,0.00003439096,0.00003455102,0.0001893845,0.003295211,0.001326576,0.00000840015,0.002999196,0.000009039651],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737067,0.0003307407,0.000582714,0.0001244803,0.00001404961,0.00002676105,0.0225407,0.0001359309,0.002537956],"genre_scores_gemma":[0.9747109,0.0002136889,0.001290249,0.00005609525,0.000007731084,0.00001620572,0.02274876,0.00004110969,0.000915199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03468817,"threshold_uncertainty_score":0.06978488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01572431070101655,"score_gpt":0.2082444668689188,"score_spread":0.1925201561679023,"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."}}