MétaCan
Menu
Back to cohort
Record W2053488386 · doi:10.4319/lom.2008.6.51

Comparison of methods to determine algal δ<sup>13</sup>C in freshwater

2008· article· en· W2053488386 on OpenAlexaff
Jérôme Marty, Dolors Planas

Bibliographic record

VenueLimnology and Oceanography Methods · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsAlgaeTrophic levelFractionationStable isotope ratioEnvironmental chemistryEnvironmental scienceBicarbonateBiomass (ecology)EutrophicationFood webTotal inorganic carbonDaphniaZooplanktonIsotopes of carbonCarbon dioxideBiologyBotanyChemistryEcologyTotal organic carbonNutrientPhysicsChromatography

Abstract

fetched live from OpenAlex

To accurately assess the flux of mass and energy to higher trophic levels in a food web using stable isotopes, the isotopic signature of basal sources is required. When studying aquatic food webs, it is difficult to obtain a signature for algae because of challenges associated with isolating small organisms from a bulk sample. In this study, we compared freshwater algal δ13C values obtained using five approaches from the literature. Results indicated that the signatures derived from a primary consumer such as Daphnia sp., from particulate organic carbon with a correction for algal biomass, and from isolated algal samples were comparable. By contrast, algal δ13C values based on the signature of carbon dioxide and algal carbon fractionation were significantly lower than those of the other approaches. The inconsistent values produced by this method were likely due to problems in determining fractionation values based on current models and were potentially related to bicarbonate uptake by algae.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.044
GPT teacher head0.374
Teacher spread0.330 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations73
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueLimnology and Oceanography MethodsSame topicIsotope Analysis in EcologyFrench-language works237,207