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Record W4408488009 · doi:10.5194/egusphere-egu25-9761

Are all deep reflectors Moho? A case study of the Newfoundland margin

2025· preprint· en· W4408488009 on OpenAlexaboutno aff
Laura Gómez de la Peña, César R. Ranero, Manel Prada, D. J. Shillington, Valentı́ Sallarès

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsMargin (machine learning)GeologyMohoSeismologyComputer scienceBiology

Abstract

fetched live from OpenAlex

The crustal structure of the Newfoundland-West Iberian conjugate margins has been extensively studied with seismic data and drilling legs. Recent surveys in the West Iberian margin have revealed a complex crustal architecture with continental, oceanic and exhumed mantle domains that change along the margin. In contrast, the Newfoundland margin, with lower seismic and drilling information available, remains comparatively more poorly understood. The main wide-angle and streamer SCREECH survey was acquired in 2000 and was modelled with comparative computational limitations at the time. The resulting images and model have been debated and did not unequivocally characterize the nature of the basement domains along the margin. Thus, the evolution of the deformation during rifting and the symmetry or asymmetry of the conjugate pair of margins are still discussed. The SCREECH data acquisition parameters are similar to modern data, and we took advantage of their quality to re-process, image the structure and model the seismic phases with methodologies that have been refined during the last decade. Recent developments in parallel computing and novel geophysical approaches provide now the means to obtain a new look at the structure with enhanced resolution seismic models and a mathematically-robust analysis of the data uncertainty, that was formerly difficult, if not unfeasible, to achieve. We use the SCREECH original field data, formed by three transects with coincident multichannel seismic (MCS) reflection data acquired with a 6-km streamer and wide-angle data recorded by short-period OBS and OBH spaced at ~15 km. We reprocessed the streamer data and also performed the joint inversion of streamer and wide-angle OBS/OBH seismic data, using reflections and refraction arrivals, which improved the definition of the geological units and the spatial resolution of the velocity model for each unit. We performed a statistical uncertainty analysis of the resulting model, supporting the improved reliability of the observed features. Our results reveal previously unrecognized crustal heterogeneity, including variations in crustal thickness and composition along the margin. In particular, the crustal domain classification and the COT location were done considering the existence of a deep reflector, interpreted as the Moho and defining a 4-5 km crust that was interpreted as oceanic. Our results suggest that this reflector may not represent the Moho, as the observed crustal properties are not consistent with typical oceanic crust. The integration of the MCS images with the velocity models allowed us to re-interpret the crustal structure of this margin and integrate all the observations in a refined evolution model for the West Iberian – Newfoundland conjugate margins.

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)0.001
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 score0.093
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.285
Teacher spread0.255 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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