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Record W3164296036 · doi:10.1002/essoar.10506404.1

The Case for Phytoplankton Blooms Under Antarctic Sea Ice

2021· preprint· en· W3164296036 on OpenAlexaff
Christopher Horvat, Sarah Seabrook, Antonia Cristi, Lisa Matthes, Kelsey Bisson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Manitoba
FundersNuclear Safety and Security CommissionNational Institute of Water and Atmospheric ResearchNational Aeronautics and Space Administration
KeywordsSea iceOceanographyPhytoplanktonArctic ice packArgoDrift iceAntarctic sea iceArctic sea ice declineEnvironmental scienceClimatologyCryosphereArcticGeologyEcology

Abstract

fetched live from OpenAlex

Being highly reflective and absorptive, sea ice was often assumed to prohibit upper ocean photosynthesis - yet observations in the modern Arctic reveal widespread under-ice blooms, driven by a transition to thinner, more mobile first-year sea ice - superficially similar to that found in the Southern Ocean. No studies have quantified the potential for under-sea-ice blooms at the Southern Ocean scale. Here we examine Southern Ocean light, sea ice, and ocean conditions, using 11 climate model contributions to CMIP6 and the ICESat-2 laser altimeter. We find large areas, 4 million square kilometers or more, of the sea-ice-covered Southern Ocean are hospitable to upper ocean photosynthesis. A stronger focus on these regions through field and remote sensing studies is necessary to assess the possible impact of under-ice productivity on Southern Hemisphere carbon and nutrient cycling.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.239
Teacher spread0.219 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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