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Record W2045460713 · doi:10.1139/f08-142

Littoral zones as sources of biodegradable dissolved organic carbon in lakes

2008· article· en· W2045460713 on OpenAlexvenueno aff
Edward G. Stets, James B. Cotner

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersMinnesota Department of Natural Resources
KeywordsLittoral zoneDissolved organic carbonMacrophyteTrophic levelTotal organic carbonEnvironmental scienceEnvironmental chemistryHydrology (agriculture)EcologyChemistryBiologyGeology

Abstract

fetched live from OpenAlex

A survey of 12 lakes in Minnesota, USA, was conducted to examine the factors controlling variability in biodegradable dissolved organic carbon (BDOC) concentration. The principal question addressed was whether BDOC concentration was more strongly related to lake trophic status or morphometric parameters. BDOC concentration was determined by incubating filtered lake water for a period of 15 months and fitting an exponential decay curve to measured DOC concentrations. BDOC concentrations varied from 73 to 427 µmol C·L–1 and composed 15%–63% of the total DOC pool. There were no significant correlations between BDOC and measures of lake trophic status. Instead, BDOC was most closely associated with the percentage of lake area covered by littoral zone, suggesting a significant source of BDOC from aquatic macrophytes and lake surface sediments.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.179
Teacher spread0.163 · 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
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

Citations29
Published2008
Admission routes1
Has abstractyes

Explore more

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