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Agriculture and Agricultural Biotechnology

2009· book-chapter· en· W2624161270 on OpenAlexaff
David Castle

Bibliographic record

VenueOxford University Press eBooks · 2009
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAgricultureAgricultural biotechnologyIntellectual propertyBiotechnologyDiversity (politics)Green RevolutionAgricultural revolutionFood securityBusinessEnvironmental ethicsAgricultural sciencePolitical scienceBiologyEcologyLaw

Abstract

fetched live from OpenAlex

Abstract This article explores a number of issues in agriculture and agricultural biotechnology putting a special emphasis within the philosophy of biology which is a fruitful area of study. The ecological impact of agriculture and the potential for humans to make novel contributions to genetic diversity raises questions about biodiversity. Thousands of years of selective breeding and food production using microorganisms in wine, bread, and cheese qualify as agricultural biotechnology. There are various disputes regarding genetically modified food, between products of agricultural biotechnology, and their conventional counterparts. The agricultural revolution also raises many ethical issues including concerns about corporate control, intellectual property rights, and use of traditional biological knowledge. We are on the threshold of the life sciences revolution. Unrevealing these mysteries of science will increase our knowledge and provide understanding of the world around us. Thus, it should lead to a better quality of life.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0240.008

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 head0.020
GPT teacher head0.181
Teacher spread0.161 · 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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