MétaCan
Menu
Back to cohort
Record W3048728002 · doi:10.1071/ma20039

A decade of RCPAQAP Biosecurity improving testing for biological threats in Australia

2020· article· en· W3048728002 on OpenAlexaff
Katherine A. Lau, Torsten Theis, Alexa Kaufer, Joanna L Gray, William D. Rawlinson

Bibliographic record

VenueMicrobiology Australia · 2020
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsCarbon Engineering (Canada)
FundersAustralian Government
KeywordsBiosecurityGovernment (linguistics)PreparednessBiodefenseCommonwealthBusinessPublic healthEnvironmental planningEnvironmental healthQuality (philosophy)Public relationsMedicinePolitical scienceGeographyNursing

Abstract

fetched live from OpenAlex

Biosecurity is a term broadly applied to the protection, control and accountability of biological agents and toxins to minimise the risk of their introduction through natural, unintentional (accidents) or deliberate processes. Biosecurity protection involves the engagement of all stakeholders including government, public health networks, industry, and scientific community. While the Commonwealth Government primarily manages biosecurity, it is also a shared responsibility with State and Territory governments. Rapid, accurate diagnosis is essential to informing all levels of response to biosecurity threats. External quality assurance (EQA) through proficiency testing (PT) is an indispensable tool to allow assessment of laboratory performance. This ensures laboratory capability and capacity are in a constant state of readiness to effectively detect biological threats and reduce the impact and transmission of disease. Since 2009, the Royal College of Pathologists Australasia Quality Assurance Program (RCPAQAP) has been contracted by the Australian Government Department of Health to establish a proficiency testing program (PTP) for the detection of biological threat agents. Starting out as a PTP for the detection of Bacillus anthracis, RCPAQAP Biosecurity has undergone significant transformation, thereby building and enhancing laboratory preparedness. Alterations in the program have been in line with the changing landscape of biosecurity and other emerging infectious diseases across Australia, and worldwide.

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)0.032
metaresearch head score (Gemma)0.036
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: none
Teacher disagreement score0.085
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.004
Scholarly communication0.0050.004
Open science0.0030.010
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0120.003

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 head0.242
GPT teacher head0.411
Teacher spread0.169 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueMicrobiology AustraliaSame topicViral Infections and Outbreaks ResearchFrench-language works237,207