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Record W2361833312 · doi:10.1130/g37657.1

The ancestral Mississippi drainage archived in the late Wisconsin Mississippi deep-sea fan

2016· article· en· W2361833312 on OpenAlexaboutno aff
Andrea Fildani, Matthew P. McKay, Daniel F. Stöckli, Jocalyn Clark, Mason Dykstra, Lisa D. Stockli, Angela M. Hessler

Bibliographic record

VenueGeology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceArchaeologyResearch centerHistoryGeologyComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

The response of continental-scale drainage systems to short-term (i.e., millennial-scale) climate change is unknown but has wide implications for understanding climate feedbacks and terrestrial-marine fluxes. The late Wisconsin Mississippi River to deep-sea fan of North America was one of Earth's largest sediment-routing networks during the most recent glacio-eustatic cycle. To understand late Pleistocene sediment production and dispersal related to the partly glaciated, ancestral Mississippi system, we sampled late Wisconsin deep-sea fan channel-fill and lobe deposits for detrital zircon U-Pb and (U-Th)/He double-dating analyses, from Deep Sea Drilling Project (Leg 96) cores and U.S. Geological Survey piston cores. Our results suggest a late Pleistocene glacial Mississippi system that forced a larger transfer of sediment from Cordilleran magmatic provinces and the Canadian Shield when compared to the modern drainage. This indicates a potentially more expansive and/or erosive ancestral Mississippi catchment, and the efficient dispersal of terrigenous sediment, nutrients, and solutes into the deep-sea via high-discharge meltwater and glacial-lake outbursts during ice retreat.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

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

Citations66
Published2016
Admission routes1
Has abstractyes

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