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Record W1512666032 · doi:10.7202/033065ar

Éléments d’identification des modelés fluvioglaciaires issus des débâcles glaciaires

2007· article· fr· W1512666032 on OpenAlexvenueaboutno aff
André Robitaille, Jean‐Marie Dubois

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languagefr
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

La description géomorphologique de la vallée de la Petite rivière Pikauba remodelée par une crue consécutive à la rupture du barrage Beloeil permet de mettre en lumière des transformations majeures. Le corridor fluvial touché, initialement tapissé de till épais, montre maintenant diverses formes d'érosion et de sédimentation qui révèlent d'étonnantes similitudes avec celles des modelés fluvioglaciaires de débâcle glaciaire, soit des crues fluvioglaciaires catastrophiques associées au déversement brusque et violent de lacs glaciaires. Les éléments d'identification les plus manifestes des modelés fluvioglaciaires de débâcles glaciaires sont : les cuvettes glaciolacustres asséchées, les barrages morainiques entaillés, les « accumulations en nappe de débâcle glaciaire » (terme proposé comme équivalent d'outburst deposit), les entailles d'érosion profondes dans le till, les terrasses d'érosion dans le till, les bancs et îlots de sédimentation fine, les formes d'érosion dans le roc. Les débâcles glaciaires correspondent à une activité de grande puissance pouvant provoquer de profondes modifications géomorphologiques. En conséquence, elles méritent d'être sérieusement considérées dans la reconstitution des environnements proglaciaires. L'application des éléments d'identification à quelques sites québécois a permis de révéler des modelés fluvioglaciaires de débâcle glaciaire qui n'avaient pas été interprétés ainsi au départ.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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

Citations3
Published2007
Admission routes2
Has abstractyes

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