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Record W1417280404

Of Moose and Men: A Wildlife Vet’s Pursuit of the World’s Largest Deer

2013· article· en· W1417280404 on OpenAlexaboutno aff
Teresa Bousquet

Bibliographic record

VenueEurope PMC (PubMed Central) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifeGeographyFellCartographyHistoryEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

This is Dr. Jerry Haigh’s third autobiographical book. He also published “Wrestling with Rhinos” (2002), and “The Trouble with Lions” (2008). I have read “Wrestling with Rhinos,” but have not yet had the opportunity to read “The Trouble with Lions.” I can assure you that the book has been ordered, and this omission will shortly be rectified! In “Of Moose and Men”, we join Jerry in 1975, when he is still in Africa, and is just accepting a position with the Western College of Veterinary Medicine, Saskatoon, Saskatchewan. The book describes some of his early experiences as the college’s first zoo and wildlife veterinarian, and then plunges into his work studying cervids, particularly moose, around the world. Jerry guides the reader through a wide variety of moosey topics, ranging from the origin of the name “moose,” to an extensive discussion of antlers and moose sexuality, to fascinating descriptions of various instances of tamed moose around the world. He describes some of the early challenges he faced as a moose researcher working in northern Saskatchewan. These included discussions of the types of sedatives that were used (and the difficulty in acquiring them), and an ingenious way of weighing wild moose in the field. One of my favorite parts of the book was a section regarding a study Jerry participated in, which involved darting, attaching colored collars (this is pre radio collars), and weighing wild moose in the Cumberland Delta region of Saskatchewan. Jerry and the other researchers he was working with would literally leap out of a hovering helicopter into deep snow in order to guide darted moose into open terrain! Isn’t that what everyone fantasizes about when they think of wildlife medicine? All in all, I thoroughly enjoyed this book. I was lucky enough to take a Game Ranching rotation with Jerry when I was in my final year of vet school. I was very inspired by the much broader range of veterinary medicine he introduced me to, and that experience has significantly influenced my career path since. I always wondered, however, how it was that Jerry ended up in Saskatchewan in the first place. He is from Scotland, his wife is from India, and they met in Africa. You would think they could have chosen from a wide range of much more exotic locales to call home! I am Saskatchewan-born, and I love my home province, but choosing to leave a warm, beautiful place like Kenya to come here seemed bizarre. However, Jerry’s deep love of all things antlered comes through very clearly in this book, and I think it goes a long way to explaining why they ended up here. I will say that I found the first couple of chapters a bit challenging to read. I had expected a format a bit more akin to Jerry’s first book, “Wrestling with Rhinos”, which was more focused on Jerry’s life. While “Of Moose and Men” is partially an autobiography, large portions of it sort of wander away from telling Jerry’s life story, and delve into various topics regarding moose. When I wasn’t expecting this, I felt like the story telling was a bit disjointed, but once I got used to this idea, it flowed very well. This book is definitely worth a read.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.005
Scholarly communication0.0090.014
Open science0.0010.004
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0120.003

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 head0.010
GPT teacher head0.176
Teacher spread0.166 · 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
Published2013
Admission routes1
Has abstractyes

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