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Record W1629799863 · doi:10.1029/2009gb003723

Importance of CO<sub>2</sub> evasion from small boreal streams

2010· article· en· W1629799863 on OpenAlexaff
J.‐F. Koprivnjak, Peter Dillon, Lewis A. Molot

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsYork UniversityTrent University
Fundersnot available
KeywordsSTREAMSBorealEnvironmental scienceAtmosphere (unit)TaigaHydrology (agriculture)Drainage basinEcologyGeologyMeteorologyGeographyBiology

Abstract

fetched live from OpenAlex

Boreal lakes are known to be supersaturated with CO 2 and to be significant sources of CO 2 to the atmosphere. In this study it is shown that small boreal streams are relatively more supersaturated with CO 2 and also represent an important source of CO 2 evasion to the atmosphere from boreal catchments. Small boreal streams account for an annual (ice‐free seasons) average of 8.0% and a seasonal high of 34.4% of the total CO 2 evaded from streams and lakes. A seasonal pattern is found, with evasion from streams being greatest during the summer and least during the spring. The evasion of CO 2 by small boreal streams represents 77% of the total CO 2 and 36% of the total organic carbon and total inorganic carbon exported by the streams from the catchments to the lakes. Knowledge of this important transfer and loss mechanism for CO 2 will allow for more accurate modeling of boreal catchment C budgets.

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 score0.113
Threshold uncertainty score0.862

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 studies0.0000.001
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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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

Citations52
Published2010
Admission routes1
Has abstractyes

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