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Record W1957552617 · doi:10.1029/2012gl053033

Cross‐regional prediction of long‐term trajectory of stream water DOC response to climate change

2012· article· en· W1957552617 on OpenAlexaff
Hjalmar Laudon, Jim Buttle, Sean K. Carey, Jeffrey J. McDonnell, K. J. McGuire, Jan Seibert, J. B. Shanley, Chris Soulsby, Doerthe Tetzlaff

Bibliographic record

VenueGeophysical Research Letters · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsGlobal Institute for Water SecurityMcMaster UniversityUniversity of SaskatchewanTrent University
FundersNorthern Research StationLeverhulme TrustU.S. Department of Agriculture
KeywordsSTREAMSDrainage basinEnvironmental scienceDissolved organic carbonClimate changeHydrology (agriculture)Surface waterLatitudeRange (aeronautics)Physical geographyGeologyOceanographyGeography

Abstract

fetched live from OpenAlex

There is no scientific consensus about how dissolved organic carbon (DOC) in surface waters is regulated. Here we combine recent literature data from 49 catchments with detailed stream and catchment process information from nine well established research catchments at mid‐ to high latitudes to examine the question of how climate controls stream water DOC. We show for the first time that mean annual temperature (MAT) in the range from −3° to +10° C has a strong control over the regional stream water DOC concentration in catchments, with highest concentrations in areas ranging between 0° and +3° C MAT. Although relatively large deviations from this model occur for individual streams, catchment topography appears to explain much of this divergence. These findings suggest that the long‐term trajectory of stream water DOC response to climate change may be more predictable than previously thought.

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)0.001
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 score0.220
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.316
Teacher spread0.267 · 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

Citations164
Published2012
Admission routes1
Has abstractyes

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