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Record W1503544344 · doi:10.7202/033105ar

Évolution postglaciaire du régime hydrosédimentaire et vitesse de l’ablation dans un petit bassin-versant des Appalaches près de Rimouski (Bas-Saint-Laurent, Québec)

2007· article· fr· W1503544344 on OpenAlexvenueaboutno aff
Bernard Hétu, P.‐Y. Le Bail

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languagefr
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyForestryGeologyArt

Abstract

fetched live from OpenAlex

L'étude stratigraphique d'un petit cône de déjection (rayon : 60 m) situé près de Rimouski, en milieu forestier, a permis de reconstituer l'évolution postglaciaire du régime hydrosédimentaire de son bassin-versant (0,145 km2) en relation avec les changements environnementaux (climat, végétation) enregistrés dans la région depuis ~11 000 ans. Le régime hydrosédimentaire de ce petit cône a changé radicalement peu avant 7200 ans BP, passant d'une sédimentation gravelo-sableuse grossièrement stratifiée à une sédimentation silto-sableuse riche en matière organique qui s'est poursuivie jusqu'à nos jours. Cette transition s'accompagne d'une diminution marquée de la vitesse de l'ablation à l'échelle du bassin-versant qui est passée de 0,0063 mm/an (= 6,3 B) entre 11 000 et 7200 ans BP à 0,0023 mm/an (= 2,3 B) après 7200 ans BP. Cette transition correspond dans le temps à la fermeture définitive du couvert forestier à l'échelle régionale, telle que révélée par les données de l'analyse pollinique. L'évolution postglaciaire du régime hydrosédimentaire de ce petit bassin-versant serait directement reliée à l'évolution du contexte écologique régional, c'est-à-dire essentiellement à l'histoire de la forêt.

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 score0.133
Threshold uncertainty score0.267

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 studies0.0010.001
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.254
Teacher spread0.236 · 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

Citations4
Published2007
Admission routes2
Has abstractyes

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