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Record W2947641223 · doi:10.1007/s10933-019-00085-1

Effects of chemical pretreatment and intra- and inter-specimen variability on δ18O of aquatic insect remains

2019· article· en· W2947641223 on OpenAlexfundno aff
Darren R. Gröcke, Scott A. Elias, Peter G. Langdon, Maarten van Hardenbroek

Bibliographic record

VenueJournal of Paleolimnology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersTanzania Commission for Science and TechnologyMcMaster University
Keywordsδ18OIsotopes of oxygenStable isotope ratioIsotopeRange (aeronautics)Environmental chemistrySeawaterBiologyEnvironmental scienceGeologyEcologyChemistryMaterials scienceGeochemistry

Abstract

fetched live from OpenAlex

Oxygen isotope (δ 18 O) measurements on the exoskeletons of aquatic insects can be used to reconstruct changes in the δ 18 O of ambient water and, indirectly, to infer the climate and environmental conditions at the time of tissue synthesis. Prior to stable isotope analysis, it is often necessary to chemically pretreat insect remains to remove allochthonous organic and inorganic compounds without altering the δ 18 O signature. We tested the effectiveness and impact of duration of exposure to a buffered 2 M ammonium chloride (NH 4 Cl) solution for removing carbonates at neutral pH from chironomid head capsules, water beetle sclerites and marine crab remains prior to stable isotope analysis. Immersion in NH 4 Cl for 24 h efficiently removed the effect of carbonates with no long-term effects of prolonged exposure observed. Furthermore, we assessed the variability in δ 18 O values within and between individual sclerites (exoskeleton parts) of both modern and fossil water beetle remains. Both modern and fossil specimens had similar intra-sclerite variability in δ 18 O values (~ 2‰ range). In contrast, modern specimens had much smaller inter-sclerite variability (< 0.9‰ range) compared with fossil specimens from the same sample (up to 10‰ range). The high inter-sclerite variability observed in fossil material likely results from the nature of fossil material: a mix of sclerites from a 1–2–L sample bin, originating from different individuals that may have existed at different times and under different environmental conditions. We therefore recommend that material to be analysed for stable isotopes be sampled at high temporal resolution to reduce uncertainties in paleotemperature estimates derived from water beetle δ 18 O records.

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 score0.064
Threshold uncertainty score0.332

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 studies0.0000.000
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 head0.004
GPT teacher head0.207
Teacher spread0.203 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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