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Record W7073944324

Familial Similarity in Aerobic Power

2020· article· en· W7073944324 on OpenAlexaboutno aff

Bibliographic record

VenueHuman Biology · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHereditySpouseSimilarity (geometry)Variation (astronomy)CorrelationRegression analysisAnalysis of variance
DOInot available

Abstract

fetched live from OpenAlex

Maximal aerobic power (MAP) exhibits considerable variation between individuals within a population. Among all causal sources contributing to variation, heredity is generally thought to exert a rather significant influence. Six hundred and seven subjects (9 to 52 years of age) from 160 families of French descent, living in the greater Quebec city area, have been measured for MAP and several related biological and cultural indicators. Subjects have been submitted to a multistage submaxi- mal ergocycle test. MAP has been estimated by regression of actual measurements of oxygen intake and heart rate (HR) at each work load to mean maximal HR. Age and sex of subjects accounted for more than 50% of the total variation in MAP. Anova procedures revealed the presence of significant familial concentrations from MAP scores adjusted for age, sex, sum of skinfolds, cigarette smoking, current energy expenditure, weekly participation in aerobic activities and socio-economic status. Inter-class correlation analysis indicated a significant spouse resemblance (r = .34), as well as a significant covariation between parents and their children (r = .19) and between children of same sibships (r = .33). These results suggest that heredity is contributing to the variation in MAP, but much less than was previously reported from twin studies.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.250
Teacher spread0.214 · 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

Citations25
Published2020
Admission routes1
Has abstractyes

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