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Record W7139649730

Fleas associated with the northern pocket gopher (<i>Thomomys talpoides</i>) in Elbert County, Colorado

2005· article· W7139649730 on OpenAlexaboutno aff
Helen K. Pigage, Jon C. Pigage, James F. Tillman

Bibliographic record

VenueScholarsArchive (Brigham Young University) · 2005
Typearticle
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsnot available
Fundersnot available
KeywordsFleaAbundance (ecology)Relative species abundanceHost (biology)RodentXenopsylla
DOInot available

Abstract

fetched live from OpenAlex

We collected 532 fleas, 526 of which were Foxella ignota ignota, from 247 northern pocket gophers, Thomomys talpoides, in Elbert County, Colorado, over 13 months. Other fleas included 1 Hystrichopsylla dippiei ssp., 3 Spicata rara, 1 Oropsylla idahoensis, and 1 female flea tentatively identified as Oropsylla (Opisocrostis) sp. These are new records for H. dippiei ssp. and S. rara in Elbert County. Fleas were cleared using standard methods and were placed on microscope slides in Canada balsam. The number of fleas per host ranged from 0 to 26. The highest median number of fleas per host (n = 5) was in May with a low median (n = 0) in August. Mean intensity and relative density of fleas peaked in April and May, respectively. Total flea abundance peaked from April through July. Approximately 72% of the male gophers (N = 99) were infested with fleas, whereas 57% of the females (N = 148) had fleas. Flea abundance on male gophers did not decrease nor did flea abundance on females increase as would be expected if flea breeding were influenced by hormones of the host. We suggest further randomized studies of fleas on T. talpoides to investigate parasite abundance throughout the year.

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 score0.306
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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
Published2005
Admission routes1
Has abstractyes

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