{"id":"W2102951277","doi":"10.1093/treephys/27.1.115","title":"Changes in net ecosystem productivity with forest age following clearcutting of a coastal Douglas-fir forest: testing a mathematical model with eddy covariance measurements along a forest chronosequence","year":2007,"lang":"en","type":"article","venue":"Tree Physiology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Trent University; University of Alberta","funders":"","keywords":"Chronosequence; Clearcutting; Primary production; Environmental science; Eddy covariance; Coarse woody debris; Ecosystem; Productivity; Litter; Douglas fir; Mineralization (soil science); Plant litter; Ecology; Botany; Soil science; Biology; Soil water","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":[0.001428106,0.0005064314,0.0002888231,0.000224101,0.0002603247,0.0006835708,0.0007085975,0.0005655502,0.0004559846],"category_scores_gemma":[0.002403634,0.0003154637,0.0005197324,0.0001598516,0.0004839235,0.0005294204,0.0002627095,0.00026634,0.00009702848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290427,"about_ca_system_score_gemma":0.0006841042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02896234,"about_ca_topic_score_gemma":0.0203661,"domain_scores_codex":[0.9998124,0.00004562951,0.00001559088,0.00007623861,0.00001609845,0.00003405919],"domain_scores_gemma":[0.9984218,0.000916704,0.0003991318,0.00005589283,0.0001357629,0.00007068986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005610944,0.0002347131,0.3763959,0.00007376035,0.0002131556,0.0002759325,0.0001939316,0.6049578,0.008410532,0.00209299,0.0002128036,0.006377414],"study_design_scores_gemma":[0.00002397255,0.0001395297,0.05606476,0.000002731842,0.00004186653,0.00004437575,0.0000301522,0.9426936,0.0006035782,0.0002830704,0.00006035792,0.00001206836],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995962,0.00003323973,0.00371804,0.00003234189,0.000002398928,0.000007183683,0.00007476744,0.00001630633,0.0001539255],"genre_scores_gemma":[0.9979848,0.00002632399,0.001728808,0.000005647501,0.00000229966,0.00001194109,0.00006415408,0.000003225508,0.0001728223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02896234,"threshold_uncertainty_score":0.0575875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.030711015617886,"score_gpt":0.2300876163810324,"score_spread":0.1993766007631464,"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."}}