{"id":"W2753848662","doi":"10.1088/1748-9326/aa8a5c","title":"Recovery time and state change of terrestrial carbon cycle after disturbance","year":2017,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service","funders":"National Natural Science Foundation of China","keywords":"Disturbance (geology); Ecosystem; Environmental science; Biomass (ecology); Deforestation (computer science); Carbon cycle; Primary production; Atmospheric sciences; Ecology; Biology; Geology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000412203,0.0001130016,0.0001242262,0.0000416179,0.0002201501,0.00006520509,0.0002871821,0.00004282441,0.0002617303],"category_scores_gemma":[0.00002097338,0.0001039965,0.00003726028,0.0000289745,0.00091339,0.0003265582,0.0006335541,0.0001997661,0.0001338428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623239,"about_ca_system_score_gemma":0.000002237801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009786315,"about_ca_topic_score_gemma":0.00006072329,"domain_scores_codex":[0.998561,0.00008943997,0.0001469941,0.0003045323,0.0005128964,0.0003851089],"domain_scores_gemma":[0.9993309,0.00004659692,0.00007725654,0.000436645,5.44673e-7,0.0001079999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003627414,0.000145668,0.8146351,0.000009958384,0.00003214399,0.0001302107,0.0006840177,0.0004501423,0.1601177,0.00000143164,0.0002124269,0.02321851],"study_design_scores_gemma":[0.0004383567,0.00009549563,0.9906974,0.00002393015,0.000006433194,0.000004621867,0.000007374433,0.005872889,0.001373238,0.0001878623,0.001118685,0.0001736471],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977115,0.00006281649,0.000003833379,0.0006732004,0.00006000167,0.0002616558,0.00009254334,0.000006404993,0.001127975],"genre_scores_gemma":[0.9987749,0.0001718885,0.00007733975,0.00007875483,0.00004548314,0.00004374691,0.00001568185,0.00001476744,0.0007774316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1760624,"threshold_uncertainty_score":0.4240856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01721763707013392,"score_gpt":0.24606190269005,"score_spread":0.2288442656199161,"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."}}