{"id":"W4239653261","doi":"10.5194/gmd-2017-169","title":"Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Environment and Climate Change Canada","funders":"","keywords":"Environmental science; Greenhouse gas; Forcing (mathematics); Climatology; Atmospheric sciences; Climate model; Precipitation; Atmosphere (unit); Climate change; Meteorology; Geography; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000646956,0.001023565,0.0004918139,0.0007385197,0.001345405,0.001537729,0.002665737,0.000751199,0.007073032],"category_scores_gemma":[0.001439768,0.0005809959,0.0009777523,0.001438313,0.0003943105,0.0009959608,0.0007690951,0.001465204,0.001212964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01020975,"about_ca_system_score_gemma":0.01786833,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9602936,"about_ca_topic_score_gemma":0.9529256,"domain_scores_codex":[0.9997163,0.00004946736,0.00001149426,0.00005954465,0.00009903492,0.00006419966],"domain_scores_gemma":[0.9993826,0.00006501685,0.00001865247,0.00003101741,0.0004238855,0.00007870897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001336851,0.00006971099,0.008630303,0.0001575172,0.0001988572,0.00007669466,0.000102585,0.9103429,0.001366573,0.01141683,0.04825613,0.01924812],"study_design_scores_gemma":[0.00008632144,0.00001144238,0.003321212,0.00002260557,0.00005069565,0.000009569306,0.00004451514,0.9738723,0.0005620497,0.001724171,0.02024352,0.0000516361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.3280004,0.002783735,0.205218,0.006333748,0.001425855,0.0009404459,0.2371627,0.02288718,0.195248],"genre_scores_gemma":[0.774755,0.001395016,0.1290502,0.0006971221,0.00007774897,0.0006367975,0.06983277,0.001904274,0.02165099],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03970641,"threshold_uncertainty_score":0.07988042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02979075450594186,"score_gpt":0.2115346089807281,"score_spread":0.1817438544747863,"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."}}