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Record W4386485529 · doi:10.3389/fmars.2023.1231083

Vertical distributions of organic matter components in sea ice near Cambridge Bay, Dease Strait, Canadian Archipelago

2023· article· en· W4386485529 on OpenAlexaffabout
Kwanwoo Kim, Sun‐Yong Ha, Kyung‐Hoon Shin, Jee‐Hoon Kim, C. J. Mundy, Laura A. Dalman, Bo Kyung Kim, Dabin Lee, Hyo Keun Jang, Yejin Kim, Sanghoon Park, Sang Heon Lee

Bibliographic record

VenueFrontiers in Marine Science · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Manitoba
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaMinistry of Oceans and FisheriesKorea Institute of Marine Science and Technology promotionKorea Polar Research InstituteNational Research Foundation
KeywordsSea iceOceanographyWater columnBiogeochemical cycleOrganic matterBayEnvironmental scienceChlorophyll aPhytoplanktonGeologyChemistryEnvironmental chemistryEcologyBiologyNutrient

Abstract

fetched live from OpenAlex

Ice algae thriving within sea ice play a crucial role in transferring energy to higher trophic levels and influencing biogeochemical processes in polar oceans; however, the distribution of organic matter within the ice interior is not well understood. This study aimed to investigate the vertical distribution of organic matter, including chlorophyll a (Chl-a), particulate organic carbon and nitrogen (POC and PON), carbohydrates (CHO), proteins (PRT), lipids (LIP), and food material (FM), within the sea ice. Samples were collected from the bottom, middle, and top sections of the sea ice column near Cambridge Bay during the spring of 2018. Based on the δ13C signature, biochemical composition, and POC contribution of biopolymeric carbon (BPC), the organic substances within the sea ice were predominantly attributed to marine autotrophs. While the highest concentrations of each parameter were observed at the sea ice bottom, notable concentrations were also found in the upper sections. The average sea ice column-integrated Chl-a concentration was 5.05 ± 2.26 mg m−2, with the bottom ice section contributing 59% (S.D. = ± 10%) to the total integration. The column-integrated concentrations of FM, BPC, POC, and PON were 2.05 ± 0.39, 1.10 ± 0.20, 1.47 ± 0.25, and 0.09 ± 0.03 g m−2, respectively. Contributions of the bottom ice section to these column-integrated concentrations varied for each parameter, with values of 20 ± 6, 21 ± 7, 19 ± 5, and 28 ± 7%, respectively. While the bottom ice section exhibited a substantial Chl-a contribution in line with previous studies, significantly higher contributions of the other parameters were observed in the upper sea ice sections. This suggests that the particulate matter within the interior of the sea ice could potentially serve as an additional food source for higher trophic grazers or act as a seeding material for a phytoplankton bloom during the ice melting season. Our findings highlight the importance of comprehensive field measurements encompassing the entire sea ice section to better understand the distribution of organic carbon pools within the sea ice in the Arctic Ocean.

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 score0.026
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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