Trajectoire des taux de mortalité aux âges extrêmes de la vie
Bibliographic record
Abstract
Au cours de la vie des adultes, les taux de mortalité par âge augmentent à un rythme assez proche du rythme exponentiel décrit par le modèle de Gompertz. Aux très grands âges, toutefois, l’évolution de ce risque de décès reste encore un sujet de débat, principalement du fait de données insuffisantes en quantité et en qualité. La disponibilité de données récentes exceptionnellement fiables pour les populations française, belge et canadienne-française au-delà de 90 ans nous donne une nouvelle opportunité de mettre à jour les connaissances sur la trajectoire de mortalité aux âges le plus élevés de la vie humaine et de tester différents modèles pour ajuster ces données. Une décélération du rythme d’accroissement des taux de mortalité est confirmée chez les femmes très âgées et les modèles de type logistique (Beard et Kannisto) donnent toujours les meilleurs ajustements. Chez les hommes, bien que les données n’écartent pas complètement ces modèles logistiques, elles sont le plus souvent ajustées de façon optimale par une croissance exponentielle de type Gompertz. Le nombre de survivants masculins trop faible aux très grands âges pourrait être à l’origine de ce résultat. Throughout adult lifespan, age-specific death rates increase at a pace which is very close to an exponential pace as depicted by the Gompertz model. At very old ages, however, changes in the risk of death remain a matter of debate, mainly because data are insufficient both in terms of quantity and quality. The availability of exceptionally reliable recent data for the French, Belgian and French-Canadian populations beyond the age of 90 gives us a new opportunity to refine our understanding of the human mortality trajectory at the highest ages and to test different models to adjust these data. A deceleration in the pace of increase of death rates is confirmed among females in very old age and logistic-type models (Beard and Kannisto) always provide the best adjustments. Among males, although the data do not completely rule out these logistic-type models, they are more often optimally described by Gompertz-type exponential growth. The low number of male survivors at very old ages could explain this result.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".