CANADIAN-MADE BINOCULARS, Part 2: BOP & CAL retrofits of RELs in the early 1950s©
Bibliographic record
Abstract
With the start of the Korean War in June 1950, the Canadian Government found itself without adequate military equipment, including binoculars. Starting in 1950, and ending in 1953, Canadian Arsenals Ltd (C.A.L.) of Long Branch, Ontario, and Beaconing Optical & Precision Materials (B.O.P.) of Granby, Quebec, were contracted to retrofit remaining or recalled WWII REL 6X30 and 7X50 binoculars. These retrofit binoculars were to provide the Canadian troops for the duration of the Korean War. Some of the 7X50s were specially modified by BOP to have internal filters (based on the British WWII 7X50 Barr & Stroud CF41): Very Dark-Dark-YellowClear for both ocular columns. Further, the optics were coated during the retrofits. The external lenses at least were coated in both the BOP and CAL (retrofits) conversions. The 6X30 REL binoculars were retrofitted with coated optics by CAL, but they underwent fewer visible changes than did the 7X50 REL binoculars by BOP. The CAL and BOP refits are indicated by the printing on both prism covers. In some cases the original REL prism cover data were deleted, either by being milled out or struck out, and can no longer be read. Often the deleted data are reprinted on another location on the prism covers. The REL 6X30 binoculars may vary in weight as much as 200g, depending on the materials used (e.g., aluminum vs brass). This is Part 2 of three articles on Canadian-made binoculars. Part 1 (Leech 2015a) discusses the WWII Research Enterprises Ltd binoculars made at Leaside, ON, and Part 3 (Leech & Kubetz 2015) discusses the 7X50 ELCAN binoculars made by Ernst Leitz Canada, of Midland, Ontario. Included is discussion of the ELCAN replacements in 1999/2000 by the 7X30 and 7X50 Fujinon binoculars which have special optical coatings and anti-laser filters for military use.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".