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Record W2087236187 · doi:10.1029/2005jg000095

Consequences of the evolution of C<sub>4</sub>photosynthesis for surface energy and water exchange

2007· article· en· W2087236187 on OpenAlexaff
Sharon A. Cowling, Colin Jones, Peter M. Cox

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiosphereEcosystemAtmospheric sciencesEnvironmental scienceAtmosphere (unit)LatitudeDry seasonPhotosynthesisClimate modelEnergy exchangeTerrestrial ecosystemClimatologyClimate changeEcologyGeologyGeographyBiologyBotanyMeteorology

Abstract

fetched live from OpenAlex

Although comprising less than 4% of all terrestrial plant species, C4plants are an essential component of low‐latitude ecosystems, and in recent modeling simulations have been shown to strongly influence the stable carbon isotope ratio of the atmosphere. We used a fully coupled Earth system model (HadCM3LC) to evaluate the contribution of C4plants to the exchange of energy and water between the biosphere and atmosphere. Our simulations indicate that the presence or absence of C4plants is important for understanding regional climate, specifically with respect to seasonal climate patterns. When C4plants are absent from simulated tropical ecosystems, the percentage of bare soil increases regionally, Amazonia becomes warmer during the dry season, South Africa becomes drier during the dry season, the African Sahara‐Sahel boundary becomes hotter during the dry season, and yet temperatures cool in central Australia during the Austral winter. Our modeling study provides the first insights into the potential climate feedbacks of late‐Miocene C4‐C3ecosystems on surface energy and water exchange.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.278
Teacher spread0.250 · 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

Citations18
Published2007
Admission routes1
Has abstractyes

Explore more

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