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Record W4214504510 · doi:10.31235/osf.io/v3wkj

Kane Tanaka’s 119 birthday and the Supercentenarians’ age estimation. Further remarks on the oldest old record of 122 years by Jeanne Calment

2022· preprint· en· W4214504510 on OpenAlexaboutno aff
Christos H. Skiadas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsCentenarianDemographyEstimationPopulationSeries (stratigraphy)GeographyStatisticsMathematicsGeologySociology

Abstract

fetched live from OpenAlex

In a previous study, based on the large number of centenarians in Japan, we had constructed a model to estimate the supercentenarians in the country, https://doi.org/10.1007/978-3-319-76002-5_2 . The model was published in Volume 46 of The Springer Series on Demographic Methods and Population Analysis. Projections are done and forecasts are made for the maximum expected age at death of record holder Kane Tanaka, now at 119 years old. Now, February 22, 2022, we have used the Saito-Ishii-Robine (2021) death data set for females (100 to 118 years old) in Japan from 1951 to 2015 to test an advanced model. We fit this model to data from 100 to 109 years of age and make projections from 110 to 119 years of age. The fit and projections apply perfectly. We have also used data from the Human Mortality Database (HMD) for female deaths (100 to +110 years old) in Japan from 1950 to 2019. The fit and projections verify the expected one supercentenarian at 119 years of age. The same model was applied to centenarian female deaths from 1950 to 2019 in a large number of countries (Europe-USA-Canada-Australia-New Zealand and Japan). By this method, a large amount of death data is selected, adequate to find extreme age supercentenarians. The fit and projections led to at least one supercentenarian at 122 years of age; that is Jeanne Calment’s record. Having estimated the two parameters of the model (slope and curvature) for these countries, we have fitted the Gerontology Research Group (GRG) database set, which led to an expectation of a supercentenarian at 120 years of age and a good probability for a 121-year-old supercentenarian in the world. A recent publication by Lenart A., Aburto J.M., Stockmarr A., Vaupel J.W. (2021) confirms our findings from 2018 regarding Calment’s record. Our provided formula estimates one supercentenarian at age 122 in the year 2045 (Skiadas, 2018) to reach the Calment’s record.

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)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0040.003

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 head0.016
GPT teacher head0.271
Teacher spread0.255 · 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 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
Published2022
Admission routes1
Has abstractyes

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