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Record W6995968834

Reconstructing Paleoenvironmental Change in Lake Scugog (Ontario, Canada) Using Subfossil Diatoms Preserved in Lake Sediments

2022· other· en· W6995968834 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSubfossilDiatomHolocenePaleolimnologyBayBenthic zoneFragilariaAssemblage (archaeology)Eutrophication
DOInot available

Abstract

fetched live from OpenAlex

Lake Scugog is a shallow impoundment in Ontario that is facing multiple stressors, especially eutrophication and climate change. This thesis used paleolimnological approaches to reconstruct diatom assemblage responses to climate change and anthropogenic stressors in the east and west basins of Lake Scugog over the last ~150 years, and in the west basin over the Holocene. The east basin experienced a diatom assemblage transition from the heavy, tychoplanktonic Aulacoisera to the small, buoyant Cyclotella likely indicating increased thermal stratification due to climate change, and an increase in small, benthic Fragilaria potentially corresponding to reduced ice cover. In Port Perry Bay, where urban development is most concentrated, small, benthic Fragilaria became dominant following the construction of the Lindsay Dam, and no other diatom assemblage changes occurred over the last ~150 years. The Holocene paleoenvironmental history of Port Perry Bay was similar to other records of Holocene climate from southern Ontario.

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 score0.016
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.162
Teacher spread0.142 · 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
Published2022
Admission routes1
Has abstractyes

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