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Record W2403024669 · doi:10.5194/bg-13-4659-2016

Inorganic carbon cycling and biogeochemical processes in an Arctic inlandsea (Hudson Bay)

2016· article· en· W2403024669 on OpenAlexafffundabout
William J. Burt, Helmuth Thomas, Lisa A. Miller, Mats A. Granskog, Tim Papakyriakou, Leah Pengelly

Bibliographic record

VenueBiogeosciences · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of ManitobaFisheries and Oceans CanadaUniversity of British ColumbiaDalhousie University
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaArcticNetKlima- og miljødepartementetFramsenteretNorsk Polarinstitutt
KeywordsBayOceanographyBiogeochemical cycleDissolved organic carbonAlkalinityTotal inorganic carbonCarbon cycleBiogeochemistrySurface waterEnvironmental scienceArcticCarbonateGeologyEcosystemCarbon dioxideEnvironmental chemistryChemistryEcology

Abstract

fetched live from OpenAlex

Abstract. The distributions of carbonate system parameters in Hudson Bay, which not only receives nearly one-third of Canada's river discharge but is also subject to annual cycles of sea-ice formation and melt, indicate that the timing and magnitude of freshwater inputs play an important role in carbon biogeochemistry and acidification in this unique Arctic ecosystem. This study uses basin-wide measurements of dissolved inorganic carbon (DIC) and total alkalinity (TA), as well as stable isotope tracers (δ18O and δ13CDIC), to provide a detailed assessment of carbon cycling processes within the bay. Surface distributions of carbonate parameters reveal the particular importance of freshwater inputs in the southern portion of the bay. Based on TA, we surmise that the deep waters in the Hudson Bay are largely of Pacific origin. Riverine TA end-members vary significantly both regionally and with small changes in near-surface depths, highlighting the importance of careful surface water sampling in highly stratified waters. In an along-shore transect, large increases in subsurface DIC are accompanied by equivalent decreases in δ13CDIC with no discernable change in TA, indicating a respiratory DIC production on the order of 100 µmol kg−1 DIC during deep water circulation around the bay.

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)0.000
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 score0.011
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.213
Teacher spread0.202 · 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

Citations32
Published2016
Admission routes3
Has abstractyes

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