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Record W1485169959 · doi:10.25011/cim.v33i2.12347

Peak expiratory flow values are higher in older and taller healthy male children: An observational study

2010· article· en· W1485169959 on OpenAlexvenueno aff
Fernanda R Radziavicius, Lourdes Conceição Martins, Camilla C Radziavicius, Vítor Engrácia Valenti, Arnaldo AF Siqueira, Cíntia G De Souza, Luíz Carlos de Abreu

Bibliographic record

VenueClinical and investigative medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePeak flow meterDemographyObservational studyInternal medicineAsthma

Abstract

fetched live from OpenAlex

PURPOSE: Peak expiratory flow (PEF) was measured in healthy children aged five to ten years in order to provide baseline values and to determine correlations between PEF and factors such as gender, age and type of school. METHODS: After the Ethical Committee of Research in Human of the School of Medicine of ABC - FMABC approval, PEF and height were measured in 1942 children between five and ten years old from nine public schools and nine private schools throughout São Bernardo do Campo City. PEF was measured using the Mini-Wright Peak Flow Meter (Clement Clarke International Ltd.) and. height was measured using a Sanny professional stadiometer . RESULTS: Significant differences were found in values for PEF: higher values were seen in older students in comparison with younger students, in males in comparison with females and in students from private schools in comparison with public schools, with average values ranging from 206 L/min to 248 L/min,. Linear correlations were seen for PEF values with both height and age (Spearman Coefficient). CONCLUSIONS: Differences were seen for PEF between genders and between types of school, and a linear correlation was seen for PEF with both age and height in healthy children from five to ten years old.

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)0.002
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.267
GPT teacher head0.400
Teacher spread0.134 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

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