{"id":"W6957933393","doi":"10.60692/v5js8-c7490","title":"GRiMeDB: The global river database of methane concentrations and fluxes","year":2022,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Fluvial; Methane; Ecosystem; Hydrology (agriculture); Ecoregion; STREAMS; Aquatic ecosystem; Spatial ecology; River ecosystem; Carbon cycle","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001352781,0.001938641,0.001994586,0.00641135,0.0004365019,0.002524071,0.002529707,0.001350073,0.02065501],"category_scores_gemma":[0.005174222,0.0008903077,0.0009171714,0.01316897,0.0002838733,0.002443552,0.002461076,0.001531327,0.02676133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008861958,"about_ca_system_score_gemma":0.002413619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02396071,"about_ca_topic_score_gemma":0.02093012,"domain_scores_codex":[0.9985079,0.0002132884,0.000334909,0.0003578052,0.0004410825,0.0001449129],"domain_scores_gemma":[0.9973826,0.0004468191,0.0007410188,0.0004505566,0.0007409214,0.0002380844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003980323,0.00005712345,0.02244079,0.004952147,0.0004848869,0.000235425,0.0002205051,0.003261438,0.001693117,0.00415619,0.9284158,0.03368454],"study_design_scores_gemma":[0.0002204879,0.00003481964,0.03106062,0.0008287153,0.000109668,0.0001106674,0.0001319624,0.002937499,0.001422504,0.003064313,0.9599612,0.0001174383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007703764,0.0003535901,0.0005708505,0.00005664345,0.00001946311,0.0000155016,0.9953837,0.001611726,0.001218148],"genre_scores_gemma":[0.003302323,0.0002633453,0.001541644,0.00004672953,0.00001287308,0.00007538474,0.9940962,0.0003141762,0.0003472987],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02396071,"threshold_uncertainty_score":0.06909788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02072952805146913,"score_gpt":0.1873397867735623,"score_spread":0.1666102587220932,"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."}}