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Record W4282931185 · doi:10.5194/gchron-4-373-2022

Simulating sedimentary burial cycles – Part 2: Elemental-based multikinetic apatite fission-track interpretation and modelling techniques illustrated using examples from northern Yukon

2022· article· en· W4282931185 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGeochronology · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
FundersNatural Resources CanadaGovernment of CanadaDalhousie UniversityWashington State University
KeywordsFission track datingGeologyApatiteMineralogyFissionSedimentary rockPaleontology

Abstract

fetched live from OpenAlex

Abstract. Compositionally dependent apatite fission track (AFT) annealing is a common but underappreciated cause for AFT age dispersion in sedimentary samples. We present an interpretation and modelling strategy for samples with variable apatite composition that exploits multikinetic AFT annealing to obtain thermal histories that can provide more detail and better resolution compared to conventional methods. We illustrate our method using a Permian and a Devonian sample from northern Yukon, Canada, both with complicated geological histories and long residence times in the AFT partial annealing zone. Effective Cl values (eCl; converted from rmr0 values) derived from detailed apatite elemental data are used to define AFT statistical kinetic populations with significantly different total annealing temperatures (∼110–185 ∘C) and ages that agree closely with the results of age mixture modelling. These AFT populations are well resolved using eCl values but exhibit significant overlap with respect to the conventional parameters of Cl content or Dpar. Elemental analyses and measured Dpar for Phanerozoic samples from Yukon and the Northwest Territories confirm that Dpar has low precision and that Cl content alone cannot account for the compositional and associated kinetic variability observed in natural samples. An inverse multikinetic AFT model, AFTINV, is used to obtain thermal-history information by simultaneously modelling multiple kinetic populations as distinct thermochronometers with different temperature sensitivities. A nondirected Monte Carlo scheme generates a set of statistically acceptable solutions at the 0.05 significance level and then these solutions are updated to the 0.5 level using a controlled random search (CRS) learning algorithm. The smoother, closer-fitting CRS solutions allow for a more consistent assessment of the eCl values and thermal-history styles that are needed to satisfy the AFT data. The high-quality Devonian sample (39 single-grain ages and 202 track lengths) has two kinetic populations that require three cycles of heating and cooling (each subsequent event of lower intensity) to obtain close-fitting solutions. The younger and more westerly Permian sample with three kinetic populations only records the latter two heating events. These results are compatible with known stratigraphic and thermal maturity constraints, and the QTQt software produces similar results. Model results for these and other samples suggest that elemental-derived eCl values are accurate within the range 0–0.25 apfu (atoms per formula unit, with rmr0 values of 0.73–0.84), which encompasses most of the data from annealing experiments. Outside of this range, eCl values for more exotic compositions may require adjustment relative to better-constrained apatite compositions when trying to fit multiple kinetic populations. Our results for natural and synthetic samples suggest that an element-based multikinetic approach has great potential to dramatically increase the temperature range and resolution of thermal histories relative to conventional AFT thermochronology.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.024
GPT teacher head0.226
Teacher spread0.202 · 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