{"id":"W4242195290","doi":"10.5194/bgd-11-6419-2014","title":"Assessing the spatial variability in peak season CO <sub>2</sub> exchange characteristics across the Arctic tundra using a light response curve parameterization","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"NordForsk; Aarhus Universitet","keywords":"Tundra; Arctic; Environmental science; Atmospheric sciences; Irradiance; Eddy covariance; Arctic vegetation; Ecosystem; Climatology; Ecology; Physics; Biology; Geology","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":[0.0005543264,0.0003189107,0.0002039968,0.0006976244,0.0001760523,0.0004775383,0.000177663,0.0002276866,0.0005200414],"category_scores_gemma":[0.000803281,0.000102002,0.0003646177,0.0006358557,0.0001037267,0.0002087451,0.0001396945,0.0001416899,0.0001802561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000341761,"about_ca_system_score_gemma":0.0001965603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02076511,"about_ca_topic_score_gemma":0.0221791,"domain_scores_codex":[0.9998363,0.00004636138,0.000009204542,0.00006516309,0.00002645121,0.00001644311],"domain_scores_gemma":[0.9995514,0.0001418078,0.00008161491,0.00009212056,0.0001079668,0.00002515124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003173989,0.00008523089,0.8669091,0.00004186257,0.0003120862,0.00007641986,0.000129411,0.0654872,0.03845709,0.0001096593,0.0002579889,0.02781655],"study_design_scores_gemma":[0.000005011202,0.0000506951,0.8958795,0.000004977641,0.00003660064,0.00008451984,0.0001068044,0.0984172,0.00487614,0.00005502634,0.0004685145,0.00001495101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957864,0.00003559437,0.003378078,0.000008104595,0.000001635446,0.000004140709,0.0004084024,0.00007048775,0.0003070457],"genre_scores_gemma":[0.9981164,0.00001262117,0.001023558,0.000003414395,0.000001200524,0.000004621778,0.0007312252,0.00001291636,0.00009407281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02076511,"threshold_uncertainty_score":0.0412885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176588455831285,"score_gpt":0.2747066786337621,"score_spread":0.2570478330506336,"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."}}