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Record W2981351595 · doi:10.4095/306170

Inferred spring discharge characteristics of the Saguenay River, Quebec between ca. 1850 and ca. 1900 based on sediment texture proxy data

2017· report· en· W2981351595 on OpenAlexaffabout
C T Schafer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsProxy (statistics)Spring (device)GeologySedimentTexture (cosmology)Hydrology (agriculture)Physical geographyGeomorphologyGeographyGeotechnical engineeringArtificial intelligenceMathematicsComputer science

Abstract

fetched live from OpenAlex

This study explores the potential of sediment textural variation as a proxy for spring freshet magnitude variation of the Saguenay River using fine sand to fine silt fractions that have been preserved in Saguenay River prodelta sediments deposited in the northwestern sector of the Saguenay Fiord's North Arm. High sedimentation rates and particulate organic matter fluxes have created a poorly oxygenated seafloor environment in parts of the North Arm that is virtually free of bioturbating organisms thereby facilitating the preservation of identifiable yearly increments of sediment that accumulate mostly during the River's annual spring freshet. A particle size (2.3 to 6.3 phi i.e., 0.220 mm to 0.013 mm) median diameter (MD) proxy of spring freshet magnitude determined at one cm intervals in a piston core collected in 1982 reflects year-to-year variability of the River's spring freshet magnitude during the 19th and most of the 20th century. This study focuses on the second half of the 19th century during which MD data records an estimated 19 year long interval of relatively small MD's (LMDI) that is estimated to have occurred between ~1871 and ~1888. Compared to the later decades of the 20th century MD record, the second half of the 19th century and the early part of the 20th century to about 1912 shows a relatively higher frequency of larger average MD that appears to imply a more frequent occurrence of stronger spring freshet intervals of comparatively lower temporal variability. Within the 1850 - 1912 interval, the MD proxy suggests a generally decreasing freshet magnitude trend from ~1865 to ~1871 that is followed by the LMDI period of reduced freshet magnitudes featuring MDs that are typically less than 55 um. The LMDI is succeeded by a generally increasing MD sequence suggestive of stronger freshets that persists until about 1912. An explanation for the apparent relatively low freshet magnitudes and low year-to-year variability of spring freshets during the LMDI in relation to previous and following decades is tentatively assigned to lesser amounts of snowfall during January and April and to relatively warmer January and February temperatures acting in concert with relatively lower March and April temperatures. These seasonal conditions show a general correspondence to warm (positive) Atlantic Multi-decadal Oscillation (AMO) phases that occurred between 1860 and 1891. In contrast, during the 20th century, cool (negative) AMO phases seem to be linked to intervals that include some of the highest recorded 20th century Saguenay River freshets witnessed in the 1970's. An analysis of the North Atlantic Oscillation (NAO)/MD relationship yielded mixed results. Not surprisingly, contradicting results also emerged in a comparison of AMO and NAO phases with respect to late 19th century local newspaper weather reports. In general, cooler spring and fall weather and stormy conditions were often associated with negative AMO conditions and with both positive and negative NAO's.

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)0.001
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 score0.019
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.029
GPT teacher head0.271
Teacher spread0.242 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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