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Record W60537660 · doi:10.7202/705343ar

Comparaison des peuplements chironomidiens du lac de l'Abbaye obtenus par différentes méthodes d'échantillonnage. Intérêts de la récolte des exuvies nymphales

2005· article· fr· W60537660 on OpenAlexaff
Valérie Verneaux, Lotfi Aleya

Bibliographic record

VenueRevue des sciences de l eau · 2005
Typearticle
Languagefr
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsForestryBiologyGeographyArt

Abstract

fetched live from OpenAlex

Une étude des espèces chironomidiennes du lac de l'Abbaye a été effectuée au cours de l'année 1993. Le répertoire spécifique a été établi à partir de l'étude des peuplements imaginaux, nymphals et larvaires échantillonnés selon 5 méthodes: récolte des imagos au filet entomologique, récolte des exuvies nymphales, mise en élevage de stades pré-imaginaux, prélèvements de larves dans les sédiments et mise en place de substrats artificiels. Le peuplement chironomidien obtenu est constitué de 69 espèces. Une comparaison de la composition des peuplements obtenus par les différents modes d'échantillonnage permet de mettre en évidence les particularités de chaque méthode. La récolte des exuvies nymphales semble être la méthode la plus appropriée pour l'établissement d'un répertoire spécifique. Deux espèces dominantes du lac Chironomus anthracinus et Psilotanypus rufovittatus témoignent du caractère polyhumique et désoxygéné du lac. Cependant, la présence simultanée en forte proportion de Tanytarsus niger, Cladotanytarsus iucundus et C. atridorsum témoignent de la faible production pélagique et de la température froide du lac susceptible de minimiser les effets de la désoxygénation sur la communauté chironomidienne.

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)0.001
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.064
GPT teacher head0.323
Teacher spread0.259 · 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
Published2005
Admission routes1
Has abstractyes

Explore more

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