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Record W3124039138 · doi:10.1029/2020jc016578

Long‐term Trends in Dissolved Organic Matter Composition and Its Relation to Sea Ice in the Canada Basin, Arctic Ocean (2007–2017)

2021· article· en· W3124039138 on OpenAlexaffabout
Cassandra DeFrancesco, Céline Guéguen

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité de SherbrookeTrent University
Fundersnot available
KeywordsDissolved organic carbonColored dissolved organic matterEnvironmental scienceEnvironmental chemistrySea iceOrganic matterChemistryOceanographyNutrientGeologyPhytoplankton

Abstract

fetched live from OpenAlex

Abstract Absorbance and fluorescence properties of dissolved organic matter (DOM) were measured in the upper and lower polar mixed layer (UPML and LPML, respectively) over an 11‐year period (2007–2017) to assess for yearly changes in the quality and quantity of colored and fluorescent DOM (CDOM and FDOM, respectively) in relation with sea ice concentration in central Canada Basin waters. The LPML waters were enriched in CDOM, total dissolved lignin phenols, terrestrial humic‐like C1, and in microbial humic‐like C2 and C7 relative to the UPML waters ( p > 0.05). The low ice years (i.e., 2012, 2016–2017) were characterized by lower humic‐like fluorescence intensity (C4 only) and abundances relative to high ice years (i.e., 2007–2011, 2013–2015), likely the result of the preferential photoalteration of humic material when sea ice concentration was reduced. Significant time increases were found in tryptophan‐like C3 in UPML and terrestrially derived humic‐like C4 in LPML, suggesting an increase in the proteinaceous and terrigenous character of FDOM in UPML and LPML during the 11‐year period, respectively. No interannual variation in dissolved organic carbon concentration was found in LPML and UPML. Weak but positive Spearman correlations were found between the humic‐like intensities and abundances, and sea ice concentration in UPML waters, a consequence of reduced photodegradation in ice covered waters. This 11‐year survey provides the first insight into the influence of summer sea ice concentration and river runoff on the quality and quantity of CDOM and FDOM.

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 score0.174
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.273
Teacher spread0.254 · 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

Citations68
Published2021
Admission routes2
Has abstractyes

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