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Record W3101540083 · doi:10.1017/qua.2020.83

Late Pleistocene and Early Holocene aeolian deposits of Tasmania and their climatic implications

2020· article· en· W3101540083 on OpenAlexaff
Peter D. McIntosh, Christina M. Neudorf, Olav B. Lian, Adrian Slee, Brianna Walker, Rolan Eberhard, RB Doyle, Grant Dixon

Bibliographic record

VenueQuaternary Research · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsGeologyRadiocarbon datingHoloceneAeolian processesPleistoceneGlacial periodLast Glacial MaximumThermoluminescence datingPhysical geographyAridPopulationBayOceanographyPaleontologyGeography

Abstract

fetched live from OpenAlex

Abstract Late Pleistocene and Early Holocene aeolian deposits in Tasmania are extensive in the present subhumid climate zone but also occur in areas receiving >1000 mm of rain annually. Thermoluminescence, optically stimulated luminescence, and radiocarbon ages indicate that most of the deposits formed during periods of cold climate. Some dunes are remnants of longitudinal desert dunes sourced from now-inundated continental shelves which were previously semi-arid. Others formed near source, often in the form of lunettes east of seasonally-dry lagoons in the previously semi-arid Midlands and southeast of Tasmania, or as accumulations close to floodplains of major rivers, or as sandsheets in exposed areas. Burning of vegetation by the Aboriginal population after 40 ka is likely to have influenced sediment supply. A key site for determining climate variability in southern Tasmania is Maynes Junction which records three periods of aeolian deposition (at ca. 90, 32 and 20 ka), interspersed with periods of hillslope instability. Whether wind speeds were higher than at present during the last glacial period is uncertain, but shells in the Mary Ann Bay sandsheet near Hobart and particle size analysis of the Ainslie dunes in northeast Tasmania suggest stronger winds during the last glacial period than at present.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.082
GPT teacher head0.308
Teacher spread0.227 · 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 teacher head, 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

Citations10
Published2020
Admission routes1
Has abstractyes

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