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Record W2611991700

The building science of office surfaces: Implications for microbial community succession

2015· dissertation· en· W2611991700 on OpenAlexfundno aff
Mahnaz Zare

Bibliographic record

VenueTSpace (University of Toronto) · 2015
Typedissertation
Languageen
FieldArts and Humanities
TopicConservation Techniques and Studies
Canadian institutionsnot available
FundersArgonne National LaboratoryUniversity of TorontoNorthern Arizona UniversitySan Diego State University
KeywordsEcological successionArchitectural engineeringEcologyEngineeringEnvironmental resource managementEnvironmental scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

The Surface Project studied the microbial succession on office surfaces in nine offices in three North American cities. Building science parameters including relative humidity (RH), temperature, equilibrium relative humidity (ERH), illumination, and occupancy were measured to investigate their impact on microbial communities. Parameters were measured every five minutes over the course of a year. ERH, RH, temperature, occupancy, and illumination varied between offices, and cities which suggests that building characteristics and climate are important factors. RH, ERH, and temperature showed clear seasonal variation. The drywall ERH varied from ERH of ceiling tile and carpet and from the RH of air. Illumination was different in occupied and unoccupied offices. Occupancy did not cause that much difference in RH. Methodology analysis revealed no difference between different frequency measurements, although it is suggested that short-term intervals to be considered since long-term intervals may not show the large variation of building science parameters.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.058
GPT teacher head0.311
Teacher spread0.253 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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