Bibliographic record
Abstract
L’enfant que j’étais et les grandes personnes qui m’entouraient avaient tous une manière particulière de se raconter la myopathie et il était parfois impossible de se comprendre. Il y avait la parole scientifique, vérifiable, mesurable, dissécable qui ne s’embarrasse pas des émotions. Des mots que l’on note dans des comptes rendus médicaux mais qui sont parfois imprononçables pour un enfant et même souvent incompréhensibles. Et puis il y avait la parole du cœur, qui se passe de mots, parce qu’on n’ose l’avouer, parce que les parents veulent protéger leur enfant, parce qu’il est difficile pour un petit d’exprimer tout ce qu’il sent, tout ce qui se joue dans son corps et son esprit. Mais même dans le silence, tout parle, les regards, les corps, les décors car l’enfant s’interroge, interprète ce qu’on lui cache et ce sont parfois ses larmes qui coulent à la place des mots. Il a fallu que j’atteigne l’âge adulte pour réussir à faire parler la petite Sarah, et les mots, comme une énergie vitale, ont comblé un espace vide, trop longtemps oublié.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.037 | 0.013 |
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".