MétaCan
Menu
Back to cohort
Record W1980943103 · doi:10.1029/2009gl038778

Routing of western Canadian Plains runoff during the 8.2 ka cold event

2009· article· en· W1980943103 on OpenAlexaboutno aff
Anders E. Carlson, Peter U. Clark, Brian A. Haley, G. P. Klinkhammer

Bibliographic record

VenueGeophysical Research Letters · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsBayGeologySurface runoffForaminiferaOceanographyIce sheetClimatologyRouting (electronic design automation)

Abstract

fetched live from OpenAlex

The collapse of the Laurentide Ice Sheet over Hudson Bay ∼8.47 ka allowed the rapid drainage of glacial Lake Agassiz into the Labrador Sea, an event identified as causing a reduction in Atlantic meridional overturning circulation (AMOC) and the 8.2 ka cold event. Atmosphere‐ocean models simulations based on this forcing, however, fail to reproduce several characteristics of this event, particularly its duration. Here we use planktonic foraminifera U/Ca records to document the routing of western Canadian Plains runoff that accompanied ice‐sheet collapse. Geochemical modeling of the ∼7 nmol/mol increase in U/Ca at the opening of Hudson Bay indicates an increase in freshwater discharge of 0.13 ± 0.03 Sverdrups (106 m3 s−1) from routing, a sufficient magnitude to cause an AMOC reduction. We suggest that this routing event suppressed AMOC strength for several centuries after the drainage of Lake Agassiz, explaining multi‐centennial climate anomalies associated with the 8.2 ka cold event.

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 score0.095
Threshold uncertainty score0.192

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.025
GPT teacher head0.284
Teacher spread0.259 · 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

Citations35
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicGeology and Paleoclimatology ResearchFrench-language works237,207