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Record W3124570367

Synchrotron dendrochemistry: Exploring the comparison of multi-dimensional elemental analysis methodologies on tree cores using synchrotron techniques

2020· dissertation· en· W3124570367 on OpenAlexaboutno aff
Zachary William Person

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2020
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSynchrotronTree (set theory)Synchrotron radiationMaterials scienceComputer sciencePhysicsNuclear physicsMathematics
DOInot available

Abstract

fetched live from OpenAlex

The research conducted in this thesis assesses the feasibility of using X-ray fluorescence (XRF) spectroscopy to determine concentrations (i.e., ppm and ppb) of heavy metals in tree core samples. The samples used to determine this feasibility came from the arsenic (As)-laden region of Yellowknife, NT, which has had past gold mining activity for several decades. With an area of known As contamination, it was hoped that the element could be used as a tracer to determine if XRF counts could in fact be compared directly to concentrations obtained from inductively coupled plasma-mass spectrometry (ICP-MS). There were eight sample locations within the study site, and they all bordered different cardinal directions of the perimeter of the Giant Mine. At each site multiple tree cores and soil samples were taken, as well as heights and diameters of the sampled trees.\n The first manuscript is focussed on determining the best parameters for XRF spectroscopy tree core scans. Determining a methodology of conducting synchrotron dendrochemistry is important because there is little-to-no research on the best parameters to use to obtain meaningful, repeatable results. Using the IDEAS beamline at the CLS synchrotron allowed us to test XRF scanning parameters on tree cores using different preparation methods, dwell times, and core orientations with respect to incoming incident light. We were able to determine the most accurate and time-efficient way to scan tree cores using XRF without sampling and preparation methods leaving contamination on the core that could be picked up by the hypersensitive detector on the beamline. We determined that a perpendicular orientation, with a dwell time of 2 s and a jog distance of 0.25 mm resulted in the best line scans that used cores that were sanded flat by iterations of subsequent sandpaper grits.\n The second manuscript is focussed on creating a relationship between the results obtained from two heavy metal analysis methodologies used in dendrochemistry; XRF and ICP-MS. Using a synchrotron, we obtained results of what elements were present in the wood by measuring photons emitted by the individual elements when excited by incident X-rays. Using ICP-MS we sampled the same tree from the same location in time to obtain precise concentrations of heavy metals from different portions of the same tree core. Although hypothesized that a relationship between the two methodologies could be found, no correlation was found; instead, two-dimensional maps of the tree cores suggested a reason why the hypothesis was not confirmed. Two-dimensional maps indicated that elements within trees likely vary in all three dimensions in a much more random fashion than was originally expected. This variation has implications for not only specific questions in dendrochemistry like radial translocation but necessarily alters the way all past and future synchrotron dendrochronological studies should be viewed.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
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 head0.039
GPT teacher head0.269
Teacher spread0.230 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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