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Record W4289530965 · doi:10.1144/sp524

About this title - Tectonic Development, Thermal History and Hydrocarbon Habitat Models of Transform Margins: their Differences from Rifted Margins

2022· article· en· W4289530965 on OpenAlexaff
Michal Němčok, Helen Doran, A. G. Doré, L. Ledvényiová, Samuel Rybár

Bibliographic record

VenueGeological Society London Special Publications · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsGeoscience BC
Fundersnot available
KeywordsTransform faultGeologyTectonicsContinental marginMargin (machine learning)PaleontologyPassive marginRift

Abstract

fetched live from OpenAlex

Transform margins form a significant portion of Earth's continent–ocean transition and are integral to continental break-up, yet compared to other margins are poorly understood. This volume brings together new multidisciplinary research to document the structural, sedimentological and thermal evolution of transform margins, highlighting their relationship to continental structure, neighbouring oceanic segments, pull-apart basins and marginal plateaus. Special emphasis is given to the comparison of transform and rifted margins, and to the economic implications of transform margin structure and evolution. Transform case studies include the Agulhas–Falkland transform, Coromandal transform (East India), Davie margin and Limpopo transform (East Africa), Guyana transform margin, Demerara transform margin (Suriname), Romanche and St Paul transforms (equatorial Africa), Sagaing transform (Andaman Sea) and Zenith–Wallaby–Perth transform (West Australia). The broad-scale interplay between transform and rifted margin segments in the North and Central Atlantic, and Caribbean, is also examined.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.003

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 head0.026
GPT teacher head0.184
Teacher spread0.158 · 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 designTheoretical or conceptual
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

Citations5
Published2022
Admission routes1
Has abstractyes

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