MétaCan
Menu
← Back to cohort
Record W6964060135 · doi:10.25549/examiner-c44-15224

Canadian destroyer escort "Nootka", 1951

2021· dataset· en· W6964060135 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Southern California Digital Library · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsShot (pellet)SternOfficerDutyFront (military)Port (circuit theory)East coast

Abstract

fetched live from OpenAlex

11 images. Canadian destroyer escort "Nootka", 7 August 1951. Commander A.B. Fraser-Harris; "Rummy" (sea-going mascot); Lloyd Halpin (seaman); Ranney O'Laney (seaman).; Supplementary material reads: "Gershon. City desk. Note: After I made shots of Canadian D.E. showing her tying up to dock, looking from stern forward, the Commanding Officer requested that we do not use that particular shot as some highly classified secret gear had not been properly covered and would be of comfort to the enemy. All other shots from bow and beams are approved for release. No. 1 and 2: Commander A.B. Fraser-Harris, DSC, commanding the Canadian Destroyer Escort Nootka is shown leaving ship to call on Captain J.Y. Dannenberg, Naval Base Commandant, just after Nootka, first Canadian man-o-war with Korea duty behind her to return to Los Angeles Harbor. Ship is en route to base at Halifax, was in port only day. Nos. 3-4: 'Rummy' sea-going mascot picked up by shore party in Korea operation, is shown with beard champions left, Lloyd Halpin, 22, of Ottawa, Ont., A/B, and Ranney O'Laney, 23, Parrsboro, Nova Scotia, A/B. Note Japanese paper flying fish kite which ship flew as 'homeward bound pennant' in background. Other shots show general scenes as Canadian Destroyer Escort, Nootka, (named for East Coast Indian tribe) docks from Korea for brief stay en route home, Halifax, Nova Scotia".

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.401
Threshold uncertainty score0.854

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.4010.104

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.

Opus teacher head0.006
GPT teacher head0.150
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of Southern California Digital Library→French-language works237,207→