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Record W3088767997 · doi:10.4236/ojss.2020.109022

Sediment Delivery by the Yukon River to the Yukon Flats, Yukon Delta and the Bering Sea

2020· article· en· W3088767997 on OpenAlexaboutno aff
Kenneth R. Olson, James Lang

Bibliographic record

VenueOpen Journal of Soil Science · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsPermafrostSedimentHydrology (agriculture)Surface runoffGlacierErosionSedimentationEnvironmental scienceFloodplainTributaryDeposition (geology)GeologyRiparian zoneHabitatOceanographyEcologyGeomorphologyGeography

Abstract

fetched live from OpenAlex

The physical, chemical and biological attributes of the Yukon River and tributary basins impact soil erosion, sediment transport and sediment delivery. The glacier, snow and permafrost melting, runoff, erosion, transport, deposition and storage of gravelly, sandy, silty and clayey sediments determine the habitat distribution and water quality within the river channels and floodplains. The ecological functioning, with food and nutrient delivery, migratory cues, breeding, habitats, and riparian and floodplain ecological cycles are all dependent on the transported sediment at specific times of the year. Annual temperatures have been rising since the 1840s which could contribute to higher runoff water flows and greater sedimentation. The primary objective was to document the sedimentation in the Yukon watershed with little soil erosion as a result of agriculture or urban development. The causes of the soil erosion and sedimentation were permafrost, alpine glacial melting, drilling for gas and oil, road construction, gold mining, cold war military sites, pipeline construction, forest fires and steep slopes.

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 score0.657
Threshold uncertainty score0.682

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.040
GPT teacher head0.247
Teacher spread0.207 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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