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Record W2103911949 · doi:10.1136/oem.58.12.761

Air traffic noise and hypertension in Stockholm County

2001· letter· en· W2103911949 on OpenAlexaboutno aff
S Pattenden

Bibliographic record

VenueOccupational and Environmental Medicine · 2001
Typeletter
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsNoise (video)Quarter (Canadian coin)Aircraft noisePublic healthEnvironmental healthTraffic noiseDistribution (mathematics)MeteorologyDemographyGeographyMedicineSociologyNoise reductionComputer scienceMathematicsArchaeology

Abstract

fetched live from OpenAlex

On any given day, according to The Economist , over 4 million people take to the skies. A quarter of a million people are airborne at any moment.1 Health impacts of noise can begin even before birth, and with high levels and an increasing distribution of exposure, any associations between aircraft noise and morbidity are clearly of relevance to public health.2 3 Rosenlund et al (page 769) assess associations between blood pressure and aircraft noise by comparing two study populations, around Arlanda airport and in another part of Stockholm County. Noise contours are constructed over the region for maximum noise level (MNL) and an energy averaged level (FBN). Health outcomes of people living in proximity tend on …

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.387
Threshold uncertainty score0.799

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.311
Teacher spread0.279 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2001
Admission routes1
Has abstractyes

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