Bibliographic record
Abstract
Charles Guiguet -pronounced "gigay" -was a man with amusing sayings."He went on before" at the age of 84, leaving his wife Muriel and their children now adults: JoAnn, Tricia, Mark and Suzanne.He was born in Shaunavon, Saskatchewan, and attended its primary and secondary schools.His father Laurant Guiguet, and mother Marie, were from France.In 1934 the family moved to Vancouver.Three leading men in the study of Canada's birds and mammals launched Charles into the field of museum collecting.In Saskatchewan, James Munro showed him how to prepare specimens for museums.Munro was a federal biologist through the 1930s and 1940s, his territory all provinces west of Ontario, and later reduced to just British Columbia.In 1936, Canada's first government mammalogist, Rudolph Anderson in Ottawa's National Museum, hired Mack Laing who had previously collected specimens for Anderson through three summers while working westward across British Columbia close to the 49th parallel.Laing was known as an outstanding hunter and naturalist.In the field he had shown Anderson that he collected through daylight and wrote his detailed observations by campfires into the night.Again Anderson hired Laing, this time to study and collect mammals through four summers on British Columbia's northern coast, this time with an assistant.Early in that year Anderson wrote to Laing: " Mr. Charles J. Guiguet, 5337 West
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.085 | 0.034 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".