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Record W4394024822 · doi:10.5281/zenodo.10216050

Lest we forget

2018· dataset· en· W4394024822 on OpenAlexaboutno aff
norgeotloic

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typedataset
Languageen
FieldMedicine
TopicDigital Imaging in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

**"Paix et Liberté ne sont jamais acquises"** ![](https://i.imgur.com/x4iIJAq.jpg) This commemorative stela, located in [Santec](https://goo.gl/maps/4e7ppJfuPiQ2) (France), was raised in honor of the 128 sailors who lost ther life aboard the [HMCS Athabaskan](https://goo.gl/Z6CzRc) in the night of April 19th, 1944. The Athabaskan was a canadian destroyer which was sunk by the [German torpedo boat T24](https://goo.gl/5ESxwy) during an interception mission in the English Channel, and now lies at 90m depth. If you are curious about the fate of this ship, you'll find more interesting information [here](https://goo.gl/y6TynL) and [there](https://goo.gl/6P1D1v). The scan was created from 96 pictures taken with a Canon Eos-1100D, processed with Colmap and OpenMVS, and re-textured and optimized to a lower resolution (~15k triangles) with Blender and [BakeMyScan](http://bakemyscan.org). ![](https://i.imgur.com/wz8oKE4.jpg) Source: Objaverse 1.0 / Sketchfab

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.284
Threshold uncertainty score0.948

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.007
Scholarly communication0.0140.015
Open science0.0020.009
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.2840.260

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 head0.045
GPT teacher head0.293
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicDigital Imaging in MedicineFrench-language works237,207