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Record W2305634121

Enhanced inactivation of avian influenza virus at -20°C by disinfectants supplemented with calcium chloride or other antifreeze agents.

2015· article· en· W2305634121 on OpenAlexaff
Jiewen Guan, Maria Chan, Brian W. Brooks, Elizabeth Rohonczy

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsAntifreezeDisinfectantCalciumChemistryFood scienceBenzalkonium chlorideAvian influenza virusMethanolVirusBiologyChromatographyInfluenza A virus subtype H5N1VirologyOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Avian influenza outbreaks have occurred during winter months, and effective disinfection of poultry premises at freezing temperatures is needed. The commercial disinfectants Virkon and Accel, supplemented with an antifreeze agent [propylene glycol (PG), methanol (MeOH), or calcium chloride (CaCl₂)], were evaluated for their effectiveness in killing avian influenza virus (AIV) at -20°C or 21°C. An AIV suspension was applied to stainless steel disks, air-dried, and covered with a disinfectant or antifreeze agent for 5 to 30 min. Virkon (2%) and Accel (6.25%) with 30% PG, 20% MeOH, or 20% CaCl₂ inactivated 6 log₁₀ AIV within 5 min at -20°C and 21°C. At these temperatures PG and MeOH alone did not kill AIV, but the 20% CaCl₂ solution alone inactivated 5 log10 AIV within 10 min. The results suggested that CaCl₂ is potentially useful to enhance the effectiveness of disinfection of poultry facilities after outbreaks of AIV infection in warm and cold seasons.

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 score0.003
Threshold uncertainty score0.006

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)0.0010.000

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 head0.099
GPT teacher head0.342
Teacher spread0.243 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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