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Record W4404692617 · doi:10.1016/j.oneear.2024.11.001

Carbon accumulation rate peaks at 1,000-m elevation in tropical planted and regrowth forests

2024· article· en· W4404692617 on OpenAlexaff
Yongxian Su, Xueyan Li, Chaoqun Zhang, Wenting Yan, Philippe Ciais, Susan C. Cook‐Patton, Oliver L. Phillips, Jiali Shang, Alessandro Cescatti, Jingming Chen, Jane Liu, Jérôme Chave, Christopher E. Doughty, Viola Heinrich, Feng Tian, Yiqi Luo, Yi Liu, Zhen Yu, Dalei Hao, Shengli Tao, Yongguang Zhang, Zhenzhong Zeng, Raffaele Lafortezza, Yuanyuan Huang, Lei Fan, Xuhui Wang, Yuanwei Qin, Qinwei Ran, Kai Yan, Xiaoping Liu, Liyang Liu, Yuemin Yue, Jiashun Ren, Wenping Yuan, Xiuzhi Chen

Bibliographic record

VenueOne Earth · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversity of TorontoAgriculture and Agri-Food Canada
FundersNational Natural Science Foundation of China
KeywordsElevation (ballistics)Tropical forestEnvironmental scienceCarbon fibersAgroforestryForestryGeographyBiologyEcologyMathematics

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.234
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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