{"id":"W4254544507","doi":"10.5194/acp-2017-1110-supplement","title":"Supplementary material to \"2010–2015 methane trends over Canada, the United States, and Mexico observed by the GOSAT satellite: contributions from different source sectors\"","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Satellite; Methane; Environmental science; Chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007358771,0.001538383,0.001170874,0.002414361,0.0007381053,0.00173639,0.002219914,0.001292239,0.6295084],"category_scores_gemma":[0.007380448,0.0008522869,0.001223244,0.005581093,0.0002392583,0.001406564,0.001667293,0.0009205253,0.1662504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001381315,"about_ca_system_score_gemma":0.002757026,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04238339,"about_ca_topic_score_gemma":0.05866743,"domain_scores_codex":[0.999423,0.00004318911,0.00006385737,0.0001149752,0.0001955266,0.000159509],"domain_scores_gemma":[0.9956064,0.001366408,0.0003891281,0.0004559002,0.001862297,0.0003198772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006851546,0.00007689198,0.001340571,0.000494641,0.00006614006,0.00008287589,0.00002920116,0.00120542,0.0002992795,0.001361043,0.991126,0.003849481],"study_design_scores_gemma":[0.00122599,0.0001016188,0.03792084,0.0005369045,0.0000963147,0.0003334239,0.000319216,0.006635161,0.002508652,0.01113689,0.9390252,0.0001596903],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008539257,0.00004461349,0.0004855091,0.0003998725,0.0007489695,0.00002509794,0.9943777,0.0005981402,0.002466231],"genre_scores_gemma":[0.006117489,0.0001370695,0.001790591,0.0002311437,0.0003397633,0.00009970391,0.9831762,0.000716447,0.007391528],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9576166,"threshold_uncertainty_score":0.5284613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009856850209402822,"score_gpt":0.2129667780532317,"score_spread":0.2031099278438289,"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."}}