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Marine palaeoseismology from very high resolution seismic imaging: the Gondola Fault Zone (Adriatic foreland)

2009· article· en· W2026596556 on OpenAlexfundno aff
Daniela Di Bucci, Domenico Ridente, Umberto Fracassi, Fabio Trincardi, Gianluca Valensise

Bibliographic record

VenueTerra Nova · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
FundersAGE-WELL
KeywordsGeologyForeland basinSeismologyFault (geology)AnticlineStrike-slip tectonicsVertical displacementSlip (aerodynamics)TectonicsActive faultPaleontology

Abstract

fetched live from OpenAlex

Abstract We present a marine palaeoseismology analysis of a dense network of very high resolution seismic profiles along the Gondola Fault Zone (GFZ), a right‐lateral, E–W‐striking, active fault system in the Adriatic foreland. This case‐study aims to show how time and space variations in the activity of a dominantly right‐lateral fault system can be assessed using the vertical component of slip. The GFZ has been investigated for a length of 50 km. It includes two parallel subvertical fault sets and two main anticlines. The late Middle Pleistocene to Holocene vertical component of displacement along the fault is bell‐shaped, suggesting that in the long‐term the fault zone acts as a single, kinematically coherent structure. Slip rates are 0–0.18 mm a−1and vary temporally on individual segments. This variability is consistent with a model in which individual fault segments rupture independently during earthquakes with magnitudes up to 6.4 and 1.3–1.8 ka recurrence intervals.

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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.216
Teacher spread0.200 · 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

Citations24
Published2009
Admission routes1
Has abstractyes

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