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Record W7097273554

Article Condensation and Mould: The Canadian Experience

2016· article· en· W7097273554 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
Fundersnot available
KeywordsCondensationHumidityStock (firearms)Atmosphere (unit)Lead (geology)
DOInot available

Abstract

fetched live from OpenAlex

Abstract It has been estimated that up to 20 % of the UK housing stock is significantly affected by dampness and associated mould growth. The effects on the health of the occu-pants of affected homes are well documented. The recent imposition of VAT at 17.5 % on domestic fuel is generally regarded as likely to worsen the problem. However, this deteri-orating situation puts me in mind of a recent study tour to Canada where the problem of dampness in housing is being tackled very differently to the United Kingdom. Are there any lessons to be learnt? Background Condensation occurs when the atmosphere can no longer support a given amount of water vapour occasioned by a reduction in temperature, such as occurs when air is brought into contact with a colder surface or when a reduction in atmospheric tempera-ture occurs. This critical temperature/ humidity relationship is known as ’dew-point’. Condensation can lead to the growth of moulds, which can liberate spores which are proven irritants of mucous membranes, and lead to unsightly damage to surface fin-ishes. The effects upon the residents of affected dwellings include both physiologi-cal and psychological damage to those most at risk, that is to say the very young and those suffering from respiratory infections as evidenced by the Chartered Institute of Environmental Health (1989). Poor design of housing, coupled with constructional problems and new surface finishes have exacerbated the growth of con-densation in the UK since the Second World War as indicated by House Condition

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0200.010
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0210.001

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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