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Record W2086261386 · doi:10.1080/10934529.2012.650581

Temperature and moisture effect on spore emission in the fungal biofiltration of hydrophobic VOCs

2012· article· en· W2086261386 on OpenAlexfundno aff
Alberto Vergara‐Fernández, Vanida Salgado-Ísmodes, M. Gallardo Pino, Sergio Hernández, Sergio Revah

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2012
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsnot available
FundersComisión Nacional de Investigación Científica y TecnológicaUniversity of British Columbia
KeywordsBiofilterMoistureSporeEnvironmental scienceEnvironmental chemistryPulp and paper industryChemistryEnvironmental engineeringBotanyBiologyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The effect of temperature and moisture on the elimination capacity (EC), CO(2) production and spore emission by Fusarium solani was studied in biofilters packed with vermiculite and fed with n- pentane. Three temperatures (15, 25 and 35°C) were tested and the highest average EC (64 g m(-3) h(-1)) and lower emission of spores (2.0 × 10(3) CFU m(-3) air) were obtained at 25°C. The effect of moisture content of the packing material indicates that the highest EC (65 g m(-3) h(-1)) was obtained at 50 % moisture. However, lowest emission (1.3 × 10(3) CFU m(-3) air) was obtained at 80 % moisture. Furthermore, the results show that a slight decrease in spore emission was found with increasing moisture content. In all cases, the depletion of the nitrogen source in the biofilter induced the sporulation, a decay of the EC and increased spore emission.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.013
GPT teacher head0.273
Teacher spread0.259 · 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 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

Citations20
Published2012
Admission routes1
Has abstractyes

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Same venueJournal of Environmental Science and Health Part ASame topicOdor and Emission Control TechnologiesFrench-language works237,207