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Record W2600035317 · doi:10.2172/1325209

Biosafety Risk Assessment Methodology

2010· report· en· W2600035317 on OpenAlexaff
Susan Caskey, Jennifer M Gaudioso, Reynolds M. Salerno, Stefan Wagner, Mika Shigematsu, George Risi, Joe Kozlovac, Vibeke Halkjær-Knudsen, Esmeralda Prat

Bibliographic record

Venuenot available
Typereport
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsCanadian Science Centre for Human and Animal HealthPublic Health Agency of Canada
Fundersnot available
KeywordsBiosafetyRisk assessmentRisk analysis (engineering)Work (physics)Variety (cybernetics)Risk managementPersonal protective equipmentBusinessEngineeringComputer scienceMedicineComputer securityPathology

Abstract

fetched live from OpenAlex

Laboratories that work with biological agents need to manage their safety risks to persons working the laboratories and the human and animal community in the surrounding areas. Biosafety guidance defines a wide variety of biosafety risk mitigation measures, which include measures which fall under the following categories: engineering controls, procedural and administrative controls, and the use of personal protective equipment; the determination of which mitigation measures should be used to address the specific laboratory risks are dependent upon a risk assessment. Ideally, a risk assessment should be conducted in a manner which is standardized and systematic which allows it to be repeatable and comparable. A risk assessment should clearly define the risk being assessed and avoid over complication.

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)0.018
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.004
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0040.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.008

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 head0.086
GPT teacher head0.414
Teacher spread0.327 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations11
Published2010
Admission routes1
Has abstractyes

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Same topicBacillus and Francisella bacterial researchFrench-language works237,207