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Record W4415087261

Petrological and geochemical study of a magma-poor rifted margin : the Australia-Antarctica ocean-continent transition as a case study

2024· article· fr· W4415087261 on OpenAlexaboutno aff
Mélanie Ballay

Bibliographic record

Venuetheses.fr (ABES) · 2024
Typearticle
Languagefr
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMargin (machine learning)MagmaContinental marginPacific ocean
DOInot available

Abstract

fetched live from OpenAlex

Les marges passives représentent la transition intraplaque entre un domaine lithosphérique continental et un domaine lithosphérique océanique. Elles enregistrent l’arrivée des premiers produits magmatiques lors de l’océanisation et constituent ainsi de véritables archives spatio-temporelles de la rupture continentale et l’initiation de l’accrétion océanique. Pourtant, les études des marges riftées peu magmatiques sont limitées à quelques rares endroits géographiques dont les marges actuelles conjuguées d’Ibérie-Terre-Neuve et les paléo-marges téthysiennes présentes dans les Alpes. Cette thèse explore les processus complexes de la transition entre la lithosphère continentale et la lithosphère océanique au niveau de la zone Diamantine, marge passive pauvre en magma située au sud-ouest de l’Australie. Les résultats s’appuient sur des données pétrologiques et géochimiques issues de l’analyse d’échantillons dragués par les campagnes MD80 et MD110. Ils permettent de souligner l’importance de l’héritage mantellique dans la formation de ces zones, tant sur le budget magmatique des marges pauvres en magma que sur la nature des produits magmatiques émis, ainsi que des processus d’interactions liquides magmatiques et roche (i.e. refertilisation).

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 score0.076
Threshold uncertainty score0.151

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 studies0.0010.000
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 head0.039
GPT teacher head0.268
Teacher spread0.229 · 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
Published2024
Admission routes1
Has abstractyes

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