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Record W4411167345 · doi:10.1139/cjfas-2025-0009

Trapped in the ice: the formation of liquid water layers within lake ice and the effect on phytoplankton communities

2025· article· en· W4411167345 on OpenAlexafffundvenueabout
David C. Barrett, Frederick J. Wrona, Ferdous Nawar

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhytoplanktonSea iceIce formationOceanographyEnvironmental scienceMelt pondEcologyGeologyCryosphereBiologyAtmospheric sciencesIce streamNutrient

Abstract

fetched live from OpenAlex

Winter lake ice conditions are undergoing rapid changes because of alterations in global and regional hydroclimatic conditions. The traditional understanding of lake ice growth and evolution through a winter period is the downward progression of ice until air temperatures rise and melt, and breakup ensues. A unique meteorological condition of substantial mid-winter warming in the foothills of the Canadian Rockies allowed for the identification of a phenomenon where a liquid water layer was trapped between ice layers near the surface of a lake. Phytoplankton analysis identified that the interstitial water layer had a bloom of motile phytoplankton belonging to the order Chlamydomonadales . Stable isotopes suggest the upward movement of pelagic water in combination with landscape runoff contributed to the formation of the interstitial water layer. This study provides new insights and illustrates the complexities involved in understanding the physicochemical and biological mechanisms involved in shaping the winter ecology, as well as subsequent ice-free periods, of lakes under a changing climate.

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 score0.897
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.010
GPT teacher head0.199
Teacher spread0.188 · 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
Published2025
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicArctic and Antarctic ice dynamics→French-language works237,207→