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Record W6948296961 · doi:10.5061/dryad.5hqbzkhbs

Arctic warming drives striking 21st century ecosystem shifts in Great Slave Lake (Subarctic Canada), North America’s deepest lake

2023· dataset· en· W6948296961 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOpen MIND · 2023
Typedataset
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsEnvironment and Climate Change CanadaQueen's University
Fundersnot available
KeywordsBiotaEcosystemArcticDominance (genetics)Structural basinLake ecosystemGlobal warmingAquatic ecosystemPlanktonClimate change

Abstract

fetched live from OpenAlex

Great Slave Lake, one of the world’s largest and North America’s deepest lake, has undergone an aquatic ecosystem transformation in response to 21st-century accelerated Arctic warming that is unparalleled in at least the past two centuries. Algal remains from a series of high-resolution palaeolimnological records retrieved from the West Basin provide baseline limnological data that we compared to historical limnological and phycological surveys undertaken on Great Slave Lake between the 1940s and 1990s. We document the rapid restructuring of algal community composition ca. 2000 CE that is consistent with recent increases in regional air temperature, as well as declines in ice cover and wind speed, that would collectively alter habitats for aquatic biota (e.g. thermal regime, vertical mixing, turbidity, light and nutrients). This new limnological regime initiated the first observation of scaled chrysophytes and favoured the rapid proliferation of small planktonic cyclotelloid diatoms that replaced the long-established dominance of large filamentous Aulacoseira islandica in West Basin sedimentary assemblages. Such rapid transformations in the primary producers of this socio-ecologically valuable “northern Great Lake” may have widespread implications for the entire food web with unknown consequences for aquatic ecosystem functioning and fisheries, which many northern and Indigenous communities depend upon.

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.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.032
GPT teacher head0.232
Teacher spread0.200 · 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