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Record W7038843696

Investigating taxonomy and speciation of Quinqueserialis (Digenea: Notocotylidae) parasites with an integrative taxonomic approach

2019· dissertation· en· W7038843696 on OpenAlexafffundabout

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of Manitoba
FundersDirectorate for Biological SciencesGwich'in Renewable Resources BoardNatural Sciences and Engineering Research Council of CanadaCanadian Society of Zoologists
KeywordsSpecies complexTaxonomy (biology)Genetic algorithmTaxonomic rankBiological classificationEcological speciationSpecies diversitySympatric speciation
DOInot available

Abstract

fetched live from OpenAlex

Estimates of parasite diversity are inaccurate due to unrecognized cryptic species and phenotypic plasticity. Integrative taxonomy (genetics, morphology, and host use) increases the clarity of species delineation, and improves knowledge of parasite biology. I used this approach to resolve taxonomic issues and test hypotheses of speciation in a genus of trematodes, Quinqueserialis. Specimens from throughout North America were field-collected and obtained from museums. No cryptic species were found, but host-induced phenotypic plasticity was confirmed in one Q. species. I confirmed two previously documented Q. species, and revised the life cycle of one to include three novel snail hosts. A new Q. species was also discovered in northern Canada. I found that the three species were influenced differently by host specificity and geographic isolation and that further sampling is needed to understand Quinqueserialis spp divergence. I illustrated the importance of resolving the species diversity of parasites before exploring their evolutionary ecology.

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: Methods · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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
GenreMethods

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
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)→Same topicParasite Biology and Host Interactions→French-language works237,207→