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Record W3149691816

Effects of historical land cover changes on climate

2007· article· en· W3149691816 on OpenAlexaboutno aff
� Shi, Zhengguo, Xiaodong, Yin, ChongHua, Wang, ZhaoMin

Bibliographic record

Venue中国科学通报:英文版 · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsLand coverClimate changeEnvironmental scienceGeographyPhysical geographyLand useGeology
DOInot available

Abstract

fetched live from OpenAlex

为了探索人为的土地的影响,在最后千年期间在气候系统上使用,一套实验与中间的复杂性的一个地球系统模型一起被执行 -- McGill 古气候模型(MPM-2 ) 。现在的纸主要在简历上集中历史的陆地盖子变化的地球物理的效果。采伐森林的一种动态情形在农田部分(RF99 ) 基于变化被描述。模型在 0.09-0.16 deg C 的范围在全球吝啬的年度温度模仿减少,在北半球的特别 0.14-0.22 deg C 在最后 300 年期间。到 GHG 集中变化的气候系统的回答也为比较被计算。现在,造林为陆上的碳隐遁和地区性的气候的调整的改进正在成为一种重要选择。结果显示那份简历陆地盖子变化的地球物理的效果不能在对气候的评价被忽视变化。

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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