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Rapid extensive erosion of the North Alpine foreland basin at 5-4 Ma

2011· article· en· W1580955337 on OpenAlexfundno aff
Charlotte Cederbom, Peter van der Beek, Fritz Schlunegger, Hugh D. Sinclair, Onno Oncken

Bibliographic record

VenueBasin Research · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersEuropean Social FundAGE-WELLAlexander von Humboldt-Stiftung
KeywordsForeland basinMolasseGeologyNeogeneThermochronologyDenudationPaleontologyTectonicsFission track datingStructural basinErosionMagnetostratigraphyGeomorphologyLate MiocenePlateau (mathematics)Sedimentary rock

Abstract

fetched live from OpenAlex

An extensive low-temperature thermochronology study of the Swiss part of the North Alpine Foreland Basin has been conducted with the aim of deciphering the late Neogene basin development. Apatite fission-track (AFT) ages from wells located in the distal and weakly deformed Plateau Molasse reveal rapid, km-scale erosion with an onset in early Pliocene times. The distribution of erosion implies that there was a strong gradient in late Miocene deposition rates along the strike of the basin, with an increase towards the northeast. Additionally, renewed tectonic activity and km-scale out-of-sequence thrusting during Plio-Pleistocene times is indicated by AFT data from wells within the thrusted, proximal Subalpine Molasse. Several different mechanisms driving late Neogene basin erosion and accelerated erosional discharge from the European Alps have been considered in the literature. Based on our AFT results, we reevaluate previously published hypotheses, and suggest that a change in climate and/or drainage reorganisation coincided and possibly interacted with preexisting tectonic and geodynamic forces in the Alpine region.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.105
GPT teacher head0.292
Teacher spread0.187 · 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 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

Citations103
Published2011
Admission routes1
Has abstractyes

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