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Record W1527737284

Marine records of Riverine water and sediment discharge in fjords of Nunatsiavut

2011· dissertation· en· W1527737284 on OpenAlexaboutno aff
Elisabeth Kahlmeyer

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2011
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicScientific Research and Discoveries
Canadian institutionsnot available
Fundersnot available
KeywordsFjordSedimentGlacierGeologyOceanographySedimentationGlacial periodErosionSedimentary rockGeomorphologyHydrology (agriculture)Geochemistry
DOInot available

Abstract

fetched live from OpenAlex

This thesis focuses on the understanding of patterns and variability of sediment and fresh water delivery from land to sea, and sediment dispersal in the marine basins of two fjords in Northern Labrador. Multibeam and sub-bottom acoustic data and sediment cores were collected in Nachvak and Saglek fjords. Sediment cores were sub-sampled for X-radiography, grain size, and radiochemical analysis (based on the particle-bound radioisotopes ²¹⁰Pb and ¹³⁷Cs,), to study sedimentary structures and determine sediment accumulation rates. Results show that the sediments are generally mottled and fine grained. Sediment accumulation rates are on average 0.21 cm/y in Nachvak fjord and 0.26 cm/y in Saglek Fjord with temporal resolutions ranging from 15 - 68 years in Nachvak Fjord and 12 -49 years in Saglek Fjord. Mass accumulation rate values suggest that the majority of the sediment is accumulating in the center of the basins. Further analyses suggest that: postglacial sedimentation was on average constant in Nachvak Fjord; in Saglek Fjord sediment accumulation was more rapid during the last ~ 100 y as compared to post-glacial times; the main sediment source in Saglek fjord is from rivers with extensive catchments that lack glaciers, and in Nachvak fjord from smaller rivers with steep, small and presently glaciated catchments as well as from additional sources such as from the erosion of glaci-marine terraces.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.255
Teacher spread0.236 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations1
Published2011
Admission routes1
Has abstractyes

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