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Record W4392435061 · doi:10.1016/j.ehb.2024.101371

Secular trends and regional pattern in body height of Austrian conscripts born between 1961 and 2002

2024· article· en· W4392435061 on OpenAlexaff
Sylvia Kirchengast, Thomas Waldhör, Alfred Juan, Lin Yang

Bibliographic record

VenueEconomics & Human Biology · 2024
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsDemographySecular variationGeographyBody heightCohortPopulationBody weightMedicineSociology

Abstract

fetched live from OpenAlex

The human growth process is influenced not only by genetic factors but also by environmental factors. Therefore, regional differences in mean body heights may exist within a population or a state. In the present study, we described and evaluated the regional trends in mean body heights in the nine Austrian provinces over a period spanning more than four decades. Body height data of 1734569 male conscripts born in Austria with Austrian citizenship between 1961 and 2002 were anonymized and analyzed. From 1961 to 2002 birth cohorts, an overall increase in the mean body height of Austrian recruits was observed, although regional differences were evident. Regions with shorter body heights in the 1961-1963 birth cohorts showed a particularly pronounced increase in mean body heights. Meanwhile, the course of body height growth in the capital city, Vienna, was striking, where the highest body heights were documented for the 1961-1963 birth cohorts. In Vienna, mean body heights continued to decline until the 1984 birth cohort and increased again from the 1988 birth cohorts. In addition to economic factors, increased stress factors in an urban environment and a form of urban penalty are discussed as causes.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.068
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.045
GPT teacher head0.308
Teacher spread0.262 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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