Report by Miss Anna May Waters: Nurse with the Canadian Forces at Hong Kong, as Given on Board the SS Gripsholm, November 1943
Bibliographic record
Abstract
9. The men didn't get the variety we got but believe they got plenty of what they did get.Hospital 10.Had a very nice little hospital, 54 beds, but it was about the hottest spot on board shipseldom below 80 to 95 degrees.After leaving Honolulu all hospital laundry had to be done in salt water in the bath tubs and then hung up around the hospital to dry.With port-holes closed at night, it wasn't a very pleasant place to sleep.Patients had to do their own laundry (sheet, towel and pillow slip) before they were discharged.11.We averaged from 40 to 50 patients all the way across.Majority of cases were sore throats and colds.Five or six cases of trench mouth, one pneumonia, one mumps, one suspect scarlet fever, 10 VDGs*, 1 VDS** and several seasick cases.12. Had two deaths -one of the ship's crew and one of our own, Pte.Schraeder [Schrage], of RRC***, admitted with seasickness and died during the night.Discovered later that he was a diabetic.13.We were on duty from 8:00 a.m. to 8:00 p.m., taking turns going off from 12 to 4 p.m. or 4 off.Had 5 stretcher bearers who acted as orderlies and one trained orderly who did night duty all the way across.The latter was a stowaway and much to his disappointment and ours he had to go back to Canada when our escort the "Robert" returned.14.Maj.Crawford, our SMO+ and RMO++ of the WG* and Capt.Banfell, RMO of RRC, took the sick parades each morning and were on call for * Venereal Disease Gonorrhea +Senior Medical Officer ** Venereal Disease Syphilis ++Regimental Medical Officer *** Royal Rifles of Canada +Winnipeg Grenadiers A group of officers and men from the Royal Rifles of Canada who survived their imprisonment by the Japanese.Photographed at the Shampshuipo Prisoner of War Camp on the Hong Kong mainland following their release in September 1945.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".