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Record W2020735342 · doi:10.3138/jvme.30.2.96

US Agriculture Is Vulnerable to Bioterrorism

2003· article· en· W2020735342 on OpenAlexvenueno aff
Harley W. Moon, Charlotte Kirk-Baer, Michael S. Ascher, R. James Cook, David R. Franz, Marjorie A. Hoy, Donald F. Husnik, Helen H. Jensen, Kenneth H. Keller, Joshua Lederberg, L. V. Madden, Linda S. Powers, Alfred D. Steinberg, A Strating, Robert E. Smith, Jennifer Kuzma, N. Grossblatt, Laura Holliday, Derek Sweatt, Seth Strongin

Bibliographic record

VenueJournal of Veterinary Medical Education · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureEnvironmental healthMedicineMedical emergencyEnvironmental planningGeographyArchaeology

Abstract

fetched live from OpenAlex

The leadership of our nation is currently grappling with a multitude of issues related to potential future terrorist activities for which there are no easy answers. Society is increasingly dependent on advances in science and technology to facilitate the examination and development of solutions to the critical problems we face today. For more than a century, the nation has turned to the National Academies— National Academy of Sciences, National Academy of Engineering, Institute of Medicine, and National Research Council—for independent, objective scientific advice. A new report of the National Academies Board on Agriculture and Natural Resources, Countering Agricultural Bioterorrism, addresses the nation’s vulnerability to terrorist attacks against agriculture and provides recommendations for strengthening our ability to prepare and respond to such attacks.

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)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.029
GPT teacher head0.350
Teacher spread0.321 · 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
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

Citations12
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Veterinary Medical EducationSame topicBacillus and Francisella bacterial researchFrench-language works237,207