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Isotopic study of honey documents widespread plant uptake of old carbon in North America

2024· article· en· W4400439241 on OpenAlexaff
Tamás Varga, Zsófi Sajtos, Edina Baranyai, Z. Szabó, Ágota Ragyák, Mihály Molnár, A. J. T. Jull, Szilárd Szabó, Krisztina Hajduné Kosdi, István Futó, James M. Kaste

Bibliographic record

VenueThe Science of The Total Environment · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsOptech (Canada)
FundersEuropean Regional Development FundMagyar Tudományos AkadémiaEuropean CommissionNemzeti Kutatási, Fejlesztési és Innovaciós AlapRRF Foundation for Aging
KeywordsCarbon fibersIsotopes of carbonGeographyEnvironmental scienceBiologyEcologyComputer scienceTotal organic carbon

Abstract

fetched live from OpenAlex

A comprehensive understanding of carbon cycling pathways in the soil-plant system is needed to develop models that accurately predict global carbon reservoir responses to anthropogenic perturbations. Honey is a carbon-rich natural food produced by wild and managed pollinating insects all over the world; the composition of a single sample is a function of millions of pollinator-plant interactions. We studied the 13C/12C and Δ14C of 121 honey samples sourced from the United States, and found a significant older carbon contribution. The effect is observed from 25 to 45° latitude, not correlated with 13C/12C, and consistent with a previously published study on European honeys. In specific cases, the measured values were up to 20 ‰ (Δ14C) higher than the expected atmospheric 14CO2 value for the given year, which shows a significant older carbon contribution. We hypothesize that the older carbon is from plant liquids derived in part from soil carbon or stored nonstructural carbohydrates from plants, which shifts the calibrated age of the sample by 5 years or more. Our work is the first to describe the widespread occurrence of older carbon in honey and shows that radiocarbon measurements can be a powerful tool to trace carbon allocations in terrestrial food webs and detect the atmosphere-soil-plant carbon cycle contributions.

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 score0.018
Threshold uncertainty score0.036

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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