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Record W2755073752 · doi:10.1017/qua.2017.71

Exploring the use of zircon geochronology as an indicator of Laurentide Ice Sheet till provenance, Indiana, USA

2017· article· en· W2755073752 on OpenAlexaboutno aff
Christine Kassab, Samantha L. Brickles, Kathy Licht, G. William Monaghan

Bibliographic record

VenueQuaternary Research · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsZirconGeologyProvenanceGeochronologyIce sheetBedrockShieldWisconsin glaciationGlacial periodGeomorphologyPaleontologyGeochemistryPhysical geographyOceanographyIce streamCryosphere

Abstract

fetched live from OpenAlex

Abstract A pilot study was designed to evaluate the potential of zircon geochronology as a provenance indicator of till from the Lake Michigan, Saginaw, and Huron-Erie Lobes of the Laurentide Ice Sheet. Based on existing ice flow-path models, we hypothesized that till from each lobe would have different zircon age population distributions because the lobes originated from regions of the Canadian Shield with different bedrock ages. After correcting for zircon fertility, the majority of grains in all till samples are 1600–950 Ma, with ~30 % of ages >2500 Ma. This similarity means that till from the three lobes cannot be clearly differentiated based on their zircon populations. The dominant ages found and the homogeneity of distributions in the till indicates a non-Shield source and, instead, reflect an origin from some combination of underlying till and sedimentary bedrock in the Great Lakes region. Even though the datasets are small, the tills have similarities to zircon distributions in Michigan Basin rocks. This implies that a substantial fraction of zircon in till was not transported long distances from the Canadian Shield. Although zircon ages are not distinct between tills, the method provides a novel application to understand Laurentide Ice Sheet glacial erosion and transport.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.321
GPT teacher head0.370
Teacher spread0.049 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2017
Admission routes1
Has abstractyes

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