{"id":"W2511701439","doi":"","title":"Climate variability and management impacts on carbon uptake in a temperate pine forest in Eastern Canada using flux data from 2003 to 2013","year":2014,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Carbon flux; Temperate climate; Environmental science; Temperate forest; Flux (metallurgy); Forestry; Temperate rainforest; Forest management; Climate change; Carbon cycle; Atmospheric sciences; Geography; Agroforestry; Ecosystem; Ecology; Geology; Biology","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":[0.0004100538,0.0003585518,0.0002524588,0.0009550747,0.0008842052,0.001070982,0.0006165392,0.0003787485,0.0008292762],"category_scores_gemma":[0.0006442073,0.0001934801,0.0005433629,0.002308891,0.0003750567,0.0003510915,0.00036976,0.0003363264,0.0001244554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01471977,"about_ca_system_score_gemma":0.01079196,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9952414,"about_ca_topic_score_gemma":0.9971781,"domain_scores_codex":[0.9998136,0.00001206255,0.00001319412,0.0000398859,0.00004479979,0.00007636219],"domain_scores_gemma":[0.999499,0.00004376634,0.00007848134,0.0000148194,0.0002665068,0.00009732274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002209248,0.00004266744,0.9868562,0.00004065481,0.0001813822,0.0001813448,0.0005038615,0.002945091,0.001198529,0.0001809197,0.0014809,0.006167509],"study_design_scores_gemma":[0.000004445944,0.000004099118,0.9968508,0.00001473952,0.00003347014,0.00002429658,0.0005306734,0.001517819,0.0001294917,0.00002337923,0.0008576838,0.000008983795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943354,0.0003844414,0.00008472294,0.0001057627,0.000005607676,0.000007197672,0.004195252,0.00001595746,0.0008656822],"genre_scores_gemma":[0.9961683,0.0002575663,0.0001625301,0.0000351955,0.00000312083,0.000005154012,0.002518566,0.000006773691,0.0008427313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01471977,"threshold_uncertainty_score":0.1067999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01451937073392235,"score_gpt":0.2208987817764791,"score_spread":0.2063794110425567,"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."}}