SHOULD MANITOBA JOIN THE NUCLEAR CLUB? L.A. Simpson 1
Bibliographic record
Abstract
Manitoba hosts the first nuclear community in Western Canada. AECL’s Whiteshell Laboratories in Pinawa carried out research on reactor safety, waste management and a number of reactor types including small reactors for powering remote communities. The Whiteshell site is now being decommissioned but will likely remain under CNSC license for the next century. The site is ideal for a new power reactor with its location on a major river, a major transmission corridor that runs through the site, and its proximity to major markets. With the relatively small grid sizes in the Prairie Provinces, it makes sense for the provincial utilities to cooperate in the building of major projects so as not to overwhelm individual utilities with a large power rector. What is needed now is a formal feasibility study to address the economic factors in favour of a nuclear plant compared with the cost of remote hydro dams and expensive transmission costs. With nuclear expansion now envisioned both east and west of Manitoba it makes sense for the province to become involved. Because of its history and knowledgeable and supportive population Pinawa could readily host a nuclear power plant or any other nuclear operation. 1. Manitoba’s nuclear history
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.053 | 0.008 |
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".