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Record W4392535144

Déglaciation et dynamiques morpho-sédimentaires des systèmes juxtaglaciaires : exemple de la marge orientale de l'Inlandsis laurentidien depuis le Dernier maximum glaciaire

2022· preprint· fr· W4392535144 on OpenAlexaboutno aff
Pierre­‐Olivier Couette

Bibliographic record

VenueServeur des thèses de l'Université de Strasbourg (University of Strasbourg) · 2022
Typepreprint
Languagefr
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsDeglaciationIce sheetGeologyGlacial periodLast Glacial MaximumMargin (machine learning)Wisconsin glaciationGeomorphologyOceanographyIce streamPhysical geographySea iceCryosphereGeographyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Cette thèse, combinant une double approche géomorphologique et sédimentologique couplée à différentes méthodes de datation, a permis de décrypter les séquences de déglaciation de la marge orientale de l’Inlandsis laurentidien depuis le Dernier maximum glaciaire, il y environ 21 000 ans. Deux systèmes présentant des caractéristiques différentes mais représentatives de leur région ont été analysés, soit : 1) le système fjord-auge glaciaire de Clyde et l’est de l’île de Baffin; et 2) la vallée de la rivière Churchill et l’est du Québec-Labrador. De manière générale, cette thèse permet de redéfinir la chronologie de déglaciation de ces deux secteurs clés et de préciser les principaux facteurs influençant le retrait de la marge glaciaire. De plus, l’ensemble des résultats présentés permet une couverture temporelle quasi intégrale de la dernière déglaciation pour la partie orientale de l’Inlandsis laurentidien, depuis sa couverture maximale et le retrait initial de la plate-forme de glace flottante au large de l’auge glaciaire de Clyde jusqu’à sa désintégration terrestre enregistrée par le système fluvio-deltaïque de la rivière Churchill à l’Holocène.

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 score0.326
Threshold uncertainty score0.649

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.202
Teacher spread0.189 · 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
Published2022
Admission routes1
Has abstractyes

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