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Record W4411665107 · doi:10.5194/essd-2024-492

Long-term meteorological and carbon, water and energy flux data from the Boreal Ecosystem Research and Monitoring Sites, Saskatchewan, Canada

2025· preprint· en· W4411665107 on OpenAlexafffundabout
Alan Barr, T. Andrew Black, Warren Helgason, Andrew Ireson, Bruce Johnson, J. H. McCaughey, Zoran Nesic, Charmaine Hrynkiw, Amber Ross, N. Hedstrom

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsEnvironment and Climate Change CanadaQueen's UniversityUniversity of British ColumbiaGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Forest ServiceQueen's UniversityCanadian Forest ServiceStrongParks CanadaEnvironment and Climate Change CanadaGlobal Institute for Water Security, University of Saskatchewan
KeywordsBorealEnvironmental scienceTerm (time)Carbon fluxEcosystemFlux (metallurgy)Carbon cycleEnergy fluxAtmospheric sciencesClimatologyGeographyOceanographyEcologyGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. The Boreal Ecosystem Research and Monitoring Sites (BERMS) are a network of flux tower research sites located near the southern boundary of the Boreal Plains Ecozone in Saskatchewan, Canada. This network includes four principal sites that characterize the region’s dominant vegetation types: mature trembling aspen (Old Aspen, OA, 1997–2017), mature black spruce (Old Black Spruce, OBS, 1997–present), mature jack pine (Old Jack Pine, OJP, 1997–present), and a minerotrophic patterned fen (Fen, 2002–present). The dataset reported here include continuous long-term records of site meteorological variables (air temperature, humidity, barometric pressure, precipitation, wind speed and direction), vertical profiles of soil temperature and volumetric water content, surface energy balance components (soil and biomass heat fluxes, photosynthetic heat flux, and eddy covariance-derived latent and sensible heat fluxes), and carbon fluxes (net ecosystem production, gross primary productivity, and ecosystem respiration). The strengths of the data set are its length and completeness, spanning up to 27 years; the care given to the measurement of net radiation and the minor surface energy balance terms; the care given to the measurement of precipitation and other hydrologic variables; and the proximity of the sites, which enables inter-site comparisons of the responses of the carbon and water balances to climatic controls. The data are available at https://doi.org/10.20383/103.01318 (Helgason et al., 2024).

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)0.001
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: Observational
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.016
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.008
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.125
GPT teacher head0.300
Teacher spread0.175 · 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
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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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