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Record W4288096711 · doi:10.5194/esurf-2022-26-rc2

Comment on esurf-2022-26

2022· peer-review· en· W4288096711 on OpenAlexaboutno aff
Sophie Hage

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersU.S. Geological SurveyNational Park ServiceNational Science Foundation
KeywordsTributaryGeologyScalable Vector GraphicsGlacial periodPaleontologyOceanographyGeochemistryPhysical geographyGeographyCartography

Abstract

fetched live from OpenAlex

Abstract. River erosion affects the carbon cycle and thus climate by exporting terrigenous carbon to seafloor sediment and by nourishing CO2-consuming marine life. The Yukon River–Bering Sea system preserves rare source-to-sink records of these processes across profound changes in global climate during the past 5 million years (Ma). Here, we expand the terrestrial erosion record by dating terraces along the Charley River, Alaska, and explore linkages among previously published Yukon River tributary incision chronologies and Bering Sea sedimentation. Cosmogenic 26Al/10Be isochron burial ages of Charley River terraces match previously documented central Yukon River tributary incision from 2.6 to 1.6 Ma during Pliocene–Pleistocene glacial expansion, and at 1.1 Ma during the 1.2–0.7 Ma Middle Pleistocene climate transition. Bering Sea sediments preserve 2–4-fold rate increases of Yukon River-derived continental detritus, terrestrial and marine organic carbon, and silicate microfossil deposition at 2.6–2.1 and 1.1–0.8 Ma. These tightly coupled records demonstrate elevated terrigenous nutrient and carbon export and concomitant Bering Sea productivity in response to climate-forced Yukon River incision. Carbon burial related to accelerated terrestrial erosion may contribute to CO2 drawdown across the Pliocene–Pleistocene and Middle Pleistocene climate transitions observed in many proxy records worldwide.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.410
Threshold uncertainty score0.841

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0200.006
Insufficient payload (model declined to judge)0.4100.348

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 head0.054
GPT teacher head0.311
Teacher spread0.257 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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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