{"id":"W3215052354","doi":"10.3389/fenvs.2021.756603","title":"Iterative Forecasting Improves Near-Term Predictions of Methane Ebullition Rates","year":2021,"lang":"en","type":"article","venue":"Frontiers in Environmental Science","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Global Lake Ecological Observatory Network; Western Virginia Water Authority; National Science Foundation","keywords":"Environmental science; Methane; Greenhouse gas; Term (time); Atmospheric sciences; Econometrics; Ecology; Mathematics; Oceanography; Geology; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003538538,0.0002044004,0.0002345729,0.00002387892,0.0002250209,0.00004062368,0.0003471239,0.00007393559,0.0006632937],"category_scores_gemma":[0.00004365708,0.0002063214,0.00007378252,0.0006197733,0.002736643,0.0007706664,0.0004870085,0.0001805928,0.00002360719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00087275,"about_ca_system_score_gemma":0.00003304998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008514254,"about_ca_topic_score_gemma":0.00001573437,"domain_scores_codex":[0.9978573,0.0000625109,0.0003727388,0.0006276434,0.0005979389,0.0004818127],"domain_scores_gemma":[0.999343,0.00002839657,0.0001560816,0.0003111265,0.00000262005,0.0001588006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001887887,0.0003325394,0.7648194,0.000007983244,0.00001115686,0.00002830541,0.001229453,0.04353008,0.1655394,0.00001727755,0.00008663851,0.0243789],"study_design_scores_gemma":[0.0005722444,0.0001486243,0.8047313,0.00003387182,0.00002340779,0.00004468753,0.003412873,0.1539296,0.03555685,0.0006276024,0.00056155,0.0003573796],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741022,0.0001631422,0.02318952,0.00005484206,0.0003876546,0.0002070108,0.00001547158,0.00001677344,0.001863398],"genre_scores_gemma":[0.8965752,0.0001301216,0.1026225,0.00007502814,0.00001543747,0.00002295336,0.00001618525,0.00001485118,0.0005276934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1299825,"threshold_uncertainty_score":0.9999774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006771643126257161,"score_gpt":0.2040646340169508,"score_spread":0.1972929908906937,"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."}}