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Towards unravelling the Rosette agent enigma: Spread and emergence of the co-invasive host-pathogen complex, Pseudorasbora parva-Sphaerothecum destruens

2021· article· en· W3199418752 on OpenAlexaff
Marine Combe, Emira Chérif, Amélie Charrier, Barbey Bruno, Chague Martine, Carrel Georges, Chasserieau Céline, Foissy Jean-Michel, Gerard Barbara, Gozlan Zachary, Guillouët Jérôme, Hérodet Benjamin, Manon Lainé, Masseboeuf Fabrice, M. Ivan, Delphine Nicolas, Poulet Nicolas, M.J.Bernadette Jean-François, André Gilles, Gozlan Rodolphe Elie

Bibliographic record

VenueThe Science of The Total Environment · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsShipping Federation of Canada
FundersAgence Nationale de la Recherche
KeywordsBiologyInvasive speciesIntroduced speciesEcologyBiodiversityFreshwater ecosystemPopulationHost (biology)Genetic diversityEcosystemZoology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0040.012
Open science0.0020.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.228
Teacher spread0.210 · 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

Citations13
Published2021
Admission routes1
Has abstractno

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Same venueThe Science of The Total Environment→Same topicGenetic diversity and population structure→French-language works237,207→