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Record W2786451841 · doi:10.22215/etd/2016-11365

Characterization of the coastal marine environment in the vicinity of a grounded iceberg, Canadian Arctic Archipelago

2016· dissertation· en· W2786451841 on OpenAlexafffundabout
Melissa Nacke

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCarleton University
FundersFisheries and Oceans Canada
KeywordsOceanographyUpwellingIcebergWater columnPhytoplanktonArcticArchipelagoChlorophyll aSea iceContinental shelfEnvironmental scienceAlgal bloomGeologyNutrientEcologyChemistry

Abstract

fetched live from OpenAlex

This study aimed to characterize the marine environment in the vicinity of a grounded iceberg near Resolute, Nunavut, and evaluate its potential influence on the surrounding water column.A survey of the physico-chemical properties (salinity, temperature and δ 18 O, as well as nitrate, phosphate and silicic acid concentrations) and phytoplankton biomass was conducted from August 11 th to 29 th , 2014.The water column was strongly stratified throughout the study area due to sea ice melt.The iceberg's interference with the ocean currents resulted in mixing and potentially upwelling in the adjacent water column.A phytoplankton bloom, indicated by high chlorophyll a concentrations (13.7 to 21.0 mg m -3 ) and surface nutrient depletion, was observed and likely began prior to sea ice break up on August 9 th .The presence of icebergs on Arctic continental shelves may influence local coastal current dynamics, although it did not appear to influence nutrient dynamics during this study.encouraged me throughout my thesis and contributed his knowledge to the project whilst allowing me the room to also work independently.I would also like to thank my co-supervisor, Dr. Christine Michel, whose enthusiasm and charisma provided a positive and motivated learning environment.Over the past two years I have benefited greatly from Derek and Christine's constructive criticism, comments, and suggestions.My fieldwork in Resolute, Nunavut could not have been accomplished without my field assistant, Sam Brenner

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 score0.051
Threshold uncertainty score0.103

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 studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.178
Teacher spread0.172 · 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

Citations2
Published2016
Admission routes3
Has abstractyes

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