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Record W3133911663 · doi:10.1002/hyp.14109

Turkey Lakes Watershed, Ontario, Canada: 40 years of interdisciplinary whole‐ecosystem research

2021· article· en· W3133911663 on OpenAlexafffundabout
Kara L. Webster, Jason A. Leach, Paul W. Hazlett, Robert L. Fleming, Erik J. S. Emilson, Daniel Houle, Kara Chan, Fariborz Norouzian, Amanda Cole, Jason O’Brien, Karen E. Smokorowski, S. A. Nelson, Shelagh Yanni

Bibliographic record

VenueHydrological Processes · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsFisheries and Oceans CanadaEnvironment and Climate Change CanadaNatural Resources CanadaCanadian Forest Service
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsWatershedEnvironmental scienceEcosystemTemperate rainforestForest ecologyVegetation (pathology)Biogeochemical cycleHydrology (agriculture)GeographyEcologyGeology

Abstract

fetched live from OpenAlex

Abstract The Turkey Lakes Watershed (TLW) study is a federal, interdepartmental study established in 1979 to investigate the effects of acid rain on terrestrial and aquatic ecosystems. The 10.5 km 2 watershed, located in the Eastern Temperate Mixed Forest on the Canadian Shield, has been the site of multidisciplinary studies on biogeochemical and ecological processes conducted across plot to catchment scales. The whole‐ecosystem investigative approach was adopted from the outset and has allowed research to evolve from its original (and continuing) acidification focus to include investigations on the effects of climate change, forest harvesting and other forest ecosystem perturbations. The extensive scientific and support infrastructure allows for collection of a comprehensive data record essential for understanding long‐term environmental trends. Data include atmospheric deposition, meteorology, stream hydrology and chemistry, soil, pore and ground water properties, understory and overstory vegetation, lake and outflow physical and chemical properties, and aquatic macroinvertebrate and fish community composition and abundance. These data have contributed to over 400 published research papers and graduate theses. The watershed has also figured prominently in many continent‐wide comparisons advancing fundamental watershed theory. The knowledge gained at TLW has influenced pollutant emission and natural resource management policies provincially, nationally and internationally.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.617
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.259
Teacher spread0.232 · 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 teacher head, 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

Citations20
Published2021
Admission routes3
Has abstractyes

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