An English Translation of Joseph Luc Riopelle, MD, (Hôtel-Dieu of Montréal), and Jean Paul Thériault (Hôpital Général of Verdun, Québec, Canada): Sur une Forme Méconnue de Sarcome des Parties Molles: Le Rhabdomyosarcome Alvéolaire (Concerning an Unrecognized Form of Sarcoma of the Soft Tissues: Alveolar Rhabdomyosarcoma). <i>Annales d'Anatomie Pathologique</i> 1956;1:88–111.
Bibliographic record
Abstract
We believe that this is the first translation into English of the first description, in French, of a disease previously unknown. JL Riopelle and JP Thériault, both pathologists, reviewed clinical and pathologic findings in six young patients with soft tissue tumors, and contributed autopsy information on four of the patients. Only one patient was initially correctly diagnosed with rhabdomyosarcoma; the other five initially had alternative diagnoses. Because of space limitations, we have condensed the clinical and pathologic details of their 23-page, approximately 9-font article into two Tables, but have otherwise translated the complete text of this seminal paper. The journal cited above was first published in 1956 in Paris, France, and is currently published as Annales de Pathologie. Its editor is unaware of any prior English translation of this article.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".