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Global Stem Respiration Dataset archived release supporting Zhang et al., 2025

2024· dataset· en· W6955392023 on OpenAlexaboutno aff

Bibliographic record

VenueScienceDB · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRespirationLatitudeRespiration rateClimate changeAcclimatizationEnvironmental data

Abstract

fetched live from OpenAlex

This archived release corresponds to the dataset underlying the published analyses in Zhang et al. (2025)(DOI: 10.1126/science.adr9978). For broader reuse and later data expansions, please refer to the separately deposited expanded release.This dataset compiles observation data on CO2 emission from woody plant stems, including 4627 data globally, 4155 temporal data on one site, and warming experiment data. These data files were analyzed to produce the statistics and figures reported in the paper about thermal acclimation of stem respiration.The data sources from (a) data from existing datasets (TRY database, which includes the Functional Ecology of Trees (FET) dataset, ECOCRAFT dataset, Global Respiration Dataset, and Tropical Respiration Dataset), (b) data digitized from publications (journal articles and book chapters from 1966 to present), (c) data provided by coauthors.The file “GSRD_global.csv” includes individual measurements of stem respiration rate (and other correlated traits) where species and site information were provided, and with sufficient information to be able to reasonably assign geographic coordinates, and thus climate data, for each sample. Each row represents an individual respiration rate datum, with each column reflecting a distinct variable including references, latitude and longitude, climate zones, species names (authorities), genus, family, group, plant functional types, measurement methods, average temperature during the growing season, average diameter at breast height, wood density, measured temperature, surface area-based stem respiration rate, mass-based stem respiration rate, and standardized mass-based stem respiration rate at 25 degrees Celsius. To ensure all the data were processed in the same way, this dataset excluded observations without stem diameter information. The measurements are from 67 sites worldwide on 186 species, and a total of 4627 observations for global analysis.The file “GSRD_seasonal.csv” includes 4155 observations of stem respiration rate for seasonal analysis, including the species black spruce, aspen and jack pine. Lavigne and Ryan measured stem respiration during the 1994 growing season at eight sites with contrasting climates. Here is a subset including data from one site near the northern boundary of the boreal region, close to Thompson, Manitoba (55.90°N, 98.75°W), where measurements were made between May to September 1994.The file “GSRD_warmingExp.csv” includes data from a warming experiment conducted by Smith et al.. They examined the thermal acclimation of stem respiration in individuals of five different woody species acclimated to five temperatures: 15, 20, 25, 30, 35 degrees Celsius on each individual following a 7-day acclimation period.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.132
Threshold uncertainty score0.440

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1320.135

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 head0.051
GPT teacher head0.385
Teacher spread0.334 · 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 designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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