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Record W3066853100 · doi:10.1071/ma20031

Biological warfare: the history of microbial pathogens, biotoxins and emerging threats

2020· article· en· W3066853100 on OpenAlexaff
Alexa Kaufer, Torsten Theis, Katherine A. Lau, Joanna L Gray, William D. Rawlinson

Bibliographic record

VenueMicrobiology Australia · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsBiological warfareTerrorismPublicityCivilian populationOrganismPopulationBiodefenseComputer securityMedicineEnvironmental healthBiologyPolitical scienceComputer scienceLawToxicologyMicrobiology

Abstract

fetched live from OpenAlex

Bioterrorism is the deliberate misuse of a pathogen (virus, bacterium or other disease-causing microorganisms) or biotoxin (poisonous substance produced by an organism) to cause illness and death amongst the population. Bioterrorism and biological warfare (biowarfare) are terms often used interchangeably. However, bioterrorism is typically attributed to the politically motivated use of biological weapons by a rogue state, terrorist organisation or rogue individual whereas biological warfare refers to a country’s use of bioweapons. Although rare, bioterrorism is a rapidly evolving threat to global security due to significant advancements in biotechnology in recent years and the severity of agents that could be exploited. The pursuit of publicity plays a vital role in bioterrorism. The success of a biological attack is often calculated by the extent of terror resulting from the event, psychological disruption of society and political breakdown, rather than the lethal effects of the agent used.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.011
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.002

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 head0.065
GPT teacher head0.281
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2020
Admission routes1
Has abstractyes

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