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Record W2013989474 · doi:10.1006/qres.2001.2227

Diatom, Pollen, and Chemical Evidence of Postglacial Climatic Change at Big Lake, South-Central British Columbia, Canada

2001· article· en· W2013989474 on OpenAlexaffabout
Joseph Bennett, Brian F. Cumming, Peter R. Leavitt, Marian Chiu, John P. Smol, Julian M. Szeicz

Bibliographic record

VenueQuaternary Research · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of ReginaQueen's University
Fundersnot available
KeywordsPollenDiatomBiogenic silicaAridEutrophicationGeologyPalynologyArboreal locomotionPhysical geographyEcologyOceanographyNutrientGeographyPaleontologyBiologyHabitat

Abstract

fetched live from OpenAlex

Abstract Postglacial climatic conditions were inferred from cores taken from Big Lake in southern British Columbia. Low concentrations of nonarboreal pollen and pigments near the base of the core suggest that initial conditions were cool. Increases in both aquatic and terrestrial production suggest warmer and moister conditions until ∼8500 cal yr B.P. Hyposaline diatom assemblages, increases in nonarboreal pollen, and increased concentrations of pigments suggest the onset of arid conditions from ∼8500 to ∼7500 cal yr B.P. Slightly less arid conditions are inferred from ∼7500 until ∼6660 cal yr B.P. based on the diatoms, small increases and greater variability in biogenic silica and pigments, and higher percentages of arboreal pollen. At ∼6600 cal yr B.P., changes in diatoms, pigments, biogenic silica, and organic matter suggest that Big Lake became fresh, deep, and eutrophic until ∼3600 cal yr B.P., when water levels and nutrients decreased slightly. Our paleoclimatic inferences are similar to pollen-based studies until ∼6600 cal yr B.P. However, unlike these studies, our multiple lines of evidence from Big Lake imply large changes in effective moisture since 6000 cal yr B.P.

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)0.001
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 score0.011
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.100
GPT teacher head0.297
Teacher spread0.197 · 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

Citations43
Published2001
Admission routes2
Has abstractyes

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