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Record W2009901998 · doi:10.1002/ppp.402

The radar signatures and age of periglacial slope deposits, Central Highlands of Germany

2001· article· en· W2009901998 on OpenAlexaff
Jörg Völkel, Matthias Leopold, Michael C. Roberts

Bibliographic record

VenuePermafrost and Periglacial Processes · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGeologyYounger DryasRadiocarbon datingPeatHead (geology)BogGround-penetrating radarTephraGeomorphologyPreborealPhysical geographyGeochemistryPaleontologyArchaeologyGlacial periodVolcanoRadar

Abstract

fetched live from OpenAlex

Abstract Determining the age of periglacial slope deposits (head) in the Central Highlands (Mittelgebirge) of Germany is a research challenge because of the lack of dateable organics and the contentious role of the Laacher See Tephra (LST) as a dating indicator. Ground penetrating radar (GPR) and cores were used to establish the subsurface stratigraphic relationships between the peat deposits of two bogs (Totenauer Moor, Bayerischer Wald and Schwarzes Moor, Rhön) and underlying head deposits in order to provide minimum ages for the head. Radiocarbon dates were obtained from peat bogs overlying the head in the Bavarian Forest, while in the Rhön (Schwarzes Moor) LST was found bedded in the peat above the head indicating that the latter therefore, is older than Alleröd. Radar profiles show that the head is a stratigraphically continuous, not interbedded, unit beneath the peat. The lowest peat at Totenauer Moor, immediately above the Upper Head, was dated at 11,550 ± 260 yr BP thus establishing the minimum age of the Upper Head as being older than Bölling and perhaps even Older Dryas, but not Younger Dryas. The LST shards were not deposited contemporaneously with the head but were incorporated by bioturbation and mass movements. This study demonstrated the utility of GPR as a tool for imaging head deposits. Copyright © 2001 John Wiley & Sons, Ltd.

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)0.000
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 score0.012
Threshold uncertainty score0.622

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 studies0.0010.001
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Citations35
Published2001
Admission routes1
Has abstractyes

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