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Record W1978618125 · doi:10.2310/7070.2001.19499

Effects of Passive Smoking on Odour Identification in Children

2001· article· en· W1978618125 on OpenAlexvenueno aff
Benny Nageris, Itzhak Braverman, Tuvia Hadar, Maynard C. Hansen, Saul Frenkiel

Bibliographic record

VenueThe Journal of Otolaryngology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePassive smokingSmokePopulationToxicologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: The effect of passive smoking on odour identification in children has rarely been reported. This study assessed the ability of such young subjects to identify a variety of odours. METHODS: The study population consisted of 20 children, 10 who were exposed to passive smoke at home and 10 with nonsmoking parents. Ten odourants were tested: vinegar, ammonia, peppermint, roses, bleach, vanilla, cough drops, turpentine, licorice, and mothballs. Each child was presented with five test trays containing all 10 odourants in random order. RESULTS: Of the total of 500 odours presented, the control group correctly identified 396 (79%) and the study group identified 356 (71%) (p < .005). The study group tended to misidentify 4 of the 10 odourants tested, namely, vanilla, roses, mothballs, and cough drops-56 of 200 (28%), compared with 96 of 200 (48%) in the control group. This was a highly significant finding (p < .0005). CONCLUSION: This work demonstrated that children exposed to passive smoke have difficulty identifying odours in comparison with children raised in relatively smoke-free environments. The identification of four odourants, vanilla, roses, mothballs, and cough drops, was particularly diminished in this study group.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.179

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.053
GPT teacher head0.263
Teacher spread0.210 · 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 designBench or experimental
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

Citations18
Published2001
Admission routes1
Has abstractyes

Explore more

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