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Record W2753080418 · doi:10.1038/s41477-017-0006-8

Towards a universal model for carbon dioxide uptake by plants

2017· letter· en· W2753080418 on OpenAlexafffund
Han Wang, I. Colin Prentice, Trevor F. Keenan, T. W. Davis, Ian J. Wright, William K. Cornwell, Bradley Evans, Changhui Peng

Bibliographic record

VenueNature Plants · 2017
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsUniversité du Québec à Montréal
FundersLaboratory Directed Research and DevelopmentNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaOffice of ScienceMacquarie UniversityNational Science FoundationImperial College LondonUniversité LavalAustralian National Data ServiceOak Ridge National LaboratoryBiological and Environmental ResearchNational Natural Science Foundation of ChinaCanadian Foundation for Climate and Atmospheric SciencesMicrosoft ResearchLawrence Berkeley National LaboratoryAustralian GovernmentU.S. Department of EnergyInternational Institute for Applied Systems Analysis
KeywordsBiomeEcosystemEddy covariancePrimary productionEnvironmental scienceAtmospheric sciencesPhotosynthesisPlant functional typeTerrestrial ecosystemCarbon dioxideEcologyBiologyBotanyPhysics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.013
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0020.006
Open science0.0030.003
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0030.002

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 head0.020
GPT teacher head0.232
Teacher spread0.212 · 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 designSimulation or modeling
Domainnot available
GenreCommentary

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

Citations426
Published2017
Admission routes2
Has abstractno

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