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Record W3046122054

The age-trajectory of mortality for french-canadian centenarians

2016· article· en· W3046122054 on OpenAlexaboutno aff
Nadine Ouellette

Bibliographic record

VenueGerontologie et societe · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsCensusDemographyLife expectancyMortality ratePopulationGerontologyGeographyMedicineSociology
DOInot available

Abstract

fetched live from OpenAlex

With the remarkable decline in mortality among the elderly after the second half of the twentieth century, the number of centenarians has increased spectacularly in low-mortality countries. In this era of human life extension, it is becoming increasingly important to obtain precise mortality at very advanced ages. We use an exhaustive set of data on all French-Canadian centenarians born in Quebec between 1870 and 1896 and who died in Quebec between the 1970-2009 to shed new light on the age-trajectory of mortality beyond 100 years, which remains uncertain and results in significant scientific debates. Thanks to Quebec’s parish registers and Canadian census returns of 1901 and 1911, the age at death of each individual can be verified and the validated data used for our death rate calculations. These are then smoothed using a flexible P-spline approach. These data are complemented with data on septuagenarians, octogenarians, and nonagenarians in Quebec from the Canadian Human Mortality Database. Our results, limited to females due to low numbers of male survivors at very advanced ages, show that the rate of mortality increase slows down with age in this population, thereby supporting the occurrence of mortality deceleration at older ages among humans.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.373
Teacher spread0.288 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

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