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Record W7162020512 · doi:10.82308/52076

Invasion dynamics of exotic and native common reed in fresh water wetlands

2011· dissertation· en· W7162020512 on OpenAlexaboutno aff
Jean-François Denis

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsWetlandHaplotypeTransectInvasive speciesIntroduced species

Abstract

fetched live from OpenAlex

Des analyses génétiques à l'échelle du paysage indiquent que les haplotypes indigènes du roseau commun (Phragmites australis (Cav.) Trin. ex Steud.) sont menacés par un haplotype européen introduit. Cependant, les interactions compétitives entre les haplotypes introduit et indigène sont peu documentées à l'échelle des populations, en particulier dans les milieux humides d'eau douce. L'objectif du projet était d'évaluer la dynamique spatiale et temporelle des haplotypes exotique (M) et indigène (F) en milieu humide d'eau douce. Spécifiquement, l'expansion des haplotypes (1) dans les communautés végétales adjacentes, ainsi qu'à (2) la zone de contact entre des populations indigènes et exotiques, a été évaluée dans des placettes de surveillance dans la Réserve de Faune du Lac St-François, Québec, Canada. Les résultats indiquent que les deux haplotypes progressent dans les communautés adjacentes, l'exotique se densifiant cependant plus rapidement que l'indigène ce qui suggère un impact plus grand sur les communautés végétales envahies. Cependant, il n'y a pas d'évidence claire après trois ans que le roseau indigène soit déplacé par le roseau exotique aux zones de contact. Mots-clés: invasion biologique, compétition végétale, dynamique des communautés, aires protégées, réserve de faune, milieu humide, Phragmites australis.

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 score0.286
Threshold uncertainty score0.568

Distilled classifier scores by category (both heads)

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

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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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
Published2011
Admission routes1
Has abstractyes

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