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Record W2999384940 · doi:10.22215/etd/2019-13699

Understanding the impact of millennial to sub-decadal climate and limnological change on the stability of As in lacustrine sediments

2019· dissertation· en· W2999384940 on OpenAlexafffund
Braden R.B. Gregory

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaPolar Knowledge CanadaGeological Society of America
KeywordsSedimentClimate changeEnvironmental scienceSedimentary rockPrecipitationSedimentationGeologyEnvironmental chemistryGeochemistryChemistryOceanographyPaleontologyGeography

Abstract

fetched live from OpenAlex

Metal(loid)s are expected to respond to 21st century warming as their stability in lacustrine systems is indirectly influenced by regional temperature and precipitation.In the Northwest Territories (NT), arsenic (As) is a metal(loid) of environmental concern due to elevated concentrations in bedrock and widespread mining-related contamination.To characterize the response of As to long-and short-term climate variability, we developed techniques that enable high temporal resolution analyses of sediment freeze cores, and applied them to a sediment cores (CON01, CON02) recovered from Control Lake, NT.New equipment was designed to enable Itrax X-ray fluorescence (Itrax-XRF) analysis of discrete sediment samples (Chapter 2).This equipment was used to test calibration methods that convert semi-quantitative Itrax-XRF results to near-total geochemical concentrations (Chapter 3).We found that the multi-variate log-ratio calibration provided the best approximation of actual geochemical concentrations.Subsequently, equipment was designed to permit scanning of freeze-cores using Itrax-XRF (Chapter 4).To characterize millennial-scale shifts in sedimentary As concentration in response to climate change, Arcellinida and ICP-MS analysis were conducted on core CON01 that recorded 4000 yr of sedimentation (Chapter 5).Arsenic concentrations the in core were related to shifts in the proportion of organic matter and shifts in minerogenic content (Rb, K).Comparison to regional records suggests changes in temperature impacted autochtonous productivity, which is hypothesized to have influenced sedimentary As concentrations.To characterize the response of As to quasi-periodic climate oscillations, CON02 was analyzed using Itrax-XRF.Itrax-XRF data were calibrated to paired ICP-MS data, and geochemical proxies for particle size (log(Zr/Ti)), in-lake productivity (log(Ca/Ti)), and As preservation (log(As/Ti)) were examined for cyclities using spectral and wavelet analyses.Periods of 8-15, 30-60, 90-130, and 180-300 yr were observed in all proxies.These periods are temporally related to the North Atlantic Oscillation/El niño/Schwabe sunspot cycles, the Pacific Decadal Oscillation, the Gleissberg cycle, and the Suess cycle, respectively.Cross-wavelet analysis of the paleo-proxies vs. published total solar irradiance reconstructions demonstrate significant relationships, suggesting a solar influence on climate and lake sediment geochemistry in the NT.These results suggest that As sequestration is impacted by short-period climate perturbations.You took me on as an undergraduate student and put me on the path to academia.Without your guidance I would not be into science, coffee or baking as I much as I am today.Thank you to my colleagues in the Earth Science Department.Thank you (soon to be) Dr. Nasser.We (finally) made it!Thank you Dr. Macumber, the first person to call me a scientist.To Michel Haché, my best bud in Ottawa

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.125
GPT teacher head0.327
Teacher spread0.201 · 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
Published2019
Admission routes2
Has abstractyes

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