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Record W4235652701 · doi:10.32920/ryerson.14648400.v1

The role of trematode parasites as a nutritional food source for higher trophic level consumers

2021· preprint· en· W4235652701 on OpenAlexaff
Keira M. McKee

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsQueen's University
Fundersnot available
KeywordsTrophic levelBiologyFood chainPredationDaphniaFood webAquatic ecosystemZooplanktonEcologyPolyunsaturated fatty acidEcosystemAquatic insectZoologyLarvaFatty acidBiochemistry

Abstract

fetched live from OpenAlex

Recently, there has been a call for the inclusion of free-living stages of trematode parasites in food web models as they are present in high numbers in aquatic ecosystems and serve as prey for higher trophic levels. I investigated the presence of lipids in cercariae, specifically neutral energy reserve lipid stores and long-chain polyunsaturated fatty acids (LC-PUFA), as they are considered the primary energy currency in aquatic ecosystems. Cercariae of all investigated taxa contained distinct neutral lipid compositions and Ribeiroia ondatrae cercariae had significant quantities of total lipids, as well as essential fatty acids (EFA). I also investigated the viability of cercariae as prey items for dragonfly larvae (Leucorrhinia intacta) and detected indistinguishable proportions of EFA in larvae subsisting on equivalent quantities of R. ondatrae and Daphnia spp. This suggests that cercariae may contribute to nutrient subsidies in aquatic ecosystems, thereby supporting aquatic organism growth and fitness.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.319
Teacher spread0.287 · 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
Published2021
Admission routes1
Has abstractyes

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