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Record W2109866671 · doi:10.5539/ijb.v5n4p1

Comparison of Three Methods for the Quantification of Sediment Organic Carbon in Salt Marshes of the Rubicon Estuary, Tasmania, Australia

2013· article· en· W2109866671 on OpenAlexvenueno aff
Kim Beasy, JC Ellison

Bibliographic record

VenueInternational Journal of Biology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon fibersSalt marshEnvironmental scienceTotal organic carbonLoss on ignitionWetlandSedimentBlue carbonEstuaryCarbon sinkCarbon sequestrationSoil carbonTotal inorganic carbonEnvironmental chemistryCarbon dioxideSoil scienceEcologyChemistryClimate changeGeologyOceanographySoil waterMathematics

Abstract

fetched live from OpenAlex

With the increasing need to accurately quantify carbon sinks of coastal wetlands, this study compares three methods in use. Sediment cores (n = 4) were collected from three salt marsh sites of the Rubicon Estuary, Tasmania Australia and analysed for organic carbon using three methods for measuring soil C concentration. The first method of elemental analysis quantified carbon using a Thermo Finnigan EA 1112 Series Flash Elemental Analyser. The second method used the loss on ignition technique at 550°C for 4 hours and applied a standard carbon conversion. The third method used loss on ignition technique at 450°C for 8 hours and applied a standard carbon conversion. Results from each method found significantly different quantities of carbon in replicate samples, however each method differentiated similar carbon trends within datasets. Each methodology investigated was found to have a useful application in carbon science, including the broad scale use of the standard carbon conversion and the accuracy of the elemental analysis method. The application of the standard carbon conversion in this study showed an underestimate of carbon stores in salt marsh sediment. Wetlands are well known to be among the most carbon rich ecosystems of the world, however this study highlights that in some cases those carbon stores may have been underestimated, and verification may further increase the value of wetlands as carbon sinks.

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 score0.313
Threshold uncertainty score0.340

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 science0.0010.000
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 head0.045
GPT teacher head0.360
Teacher spread0.316 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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