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Record W1483748663 · doi:10.7202/032913ar

Climatic Influences of Deglacial Drainage Changes in Southern Canada at 10 to 8 ka Suggested by Pollen Evidence

2007· article· en· W1483748663 on OpenAlexvenueaboutno aff
T. W. Anderson, C F M Lewis

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMeltwaterBayOceanographyGeologyDrainagePollenVegetation (pathology)Hydrology (agriculture)Physical geographyGlacierGeomorphologyGeographyEcology

Abstract

fetched live from OpenAlex

Enhanced meltwater discharge from proglacial lakes Agassiz and Barlow-Ojibway at about 9.6 to 8.3 ka BP. created cold localized climates over downstream water bodies, specifically Lake Minong and Mattawa phase lakes in the Great Lakes and Goldthwait Sea in the Gulf of St. Lawrence. The cooling effect of the meltwater drainage suppressed summer warming of the surface lake waters, reduced the growing season and thus altered the vegetation composition in the surrounding land areas. The vegetation responded in different ways as evidenced by five variants from the normal pollen succession.The pollen anomalies are most pronounced where the effect of increased meltwater discharge had a strong influence, such as within or along the margins of Lake Agassiz, Mattawa phase lakes, and the Goldthwait Sea, or in their lee areas, especially where these water bodies intersected ecotonal boundaries. Climatic effects were minimal or non-existent where the water surface areas were restricted such as the channelized drainage routes of the Ottawa and St. Lawrence rivers. Diversion of Lakes Agassiz and Barlow-Ojibway drainage to Hudson Bay after about 8.4 ka BP reinstated summer warming of the surface water in the Great Lakes-St. Lawrence system bringing the 9.6-8.3 ka cool period to a close.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.244
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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 teacher head, 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

Citations47
Published2007
Admission routes2
Has abstractyes

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