Canadian cruiser, HMCS Ontario, arrives at Terminal Island, 1951
Bibliographic record
Abstract
8 images. Canadian cruiser, HMCS Ontario, arrives at Terminal Island, 6 December 1951. Ronald Cowan, Chief Petty Officer; Hal Stevens, Chief Petty Officer; Captain Ernest Patrick Tisdall, Royal Canadian Navy; Victor Duclos, Canadian Trade Commissioner; Captain C.E. Coffin, Junior, United States Navy; Captain Al Teague, Pilot.; Supplementary material reads: "Gershon. City desk. Illus. Canadian Cruiser Ontario. She was escort for Princess' Elizabeth's royal tour. The Canadian Cruiser Ontario is shown arriving at Naval Base, Terminal Island, en route to home base Esquimalt. No 1-2: Ontario arriving being led to dock by American tug which assisted her docking. No 3 -- Canadian sailors are shown "reeving" the line through stern chock as cruiser Ontario arrives for four day visit. No 4-5: Beard champions. Left, Chief Petty Officers Ronald Cowan and Hal Stevens, right, proudly display heavy beards grown during cruise of Canadian Cruiser Ontario. No 6 -- Bridge section of Cruiser Ontario as she arrives alongside dock. Man in civillian hat is Capt. Al Teague, pilot. who docked cruiser. No. 7-8: Left. Captain Ernest Patrick Tisdall, R.C.N., commanding cruiser Ontario greeted by Victor Duclos, center, Canadian Trade Commissioner in Los Angeles, and Captain C.E. Coffin, Jr. USN, who extended port courtesies for Captain J.Y. Dannenberg, Naval Base Cammandant, now on leave".
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.634 | 0.231 |
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".