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Record W1538904618 · doi:10.22004/ag.econ.46357

Using Biotechnology to Lower Production Costs of Biofuels in Canada: Will it Hinder the Growth of an Export Industry?

2006· article· en· W1538904618 on OpenAlexaboutno aff
Laura J. Loppacher

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsBiofuelBiosafetyProduction (economics)International tradeBusinessEnergy securityNatural resource economicsBiotechnologyIndustrial organizationEconomicsAgricultural economicsCommerceEngineeringRenewable energy

Abstract

fetched live from OpenAlex

Bio-based fuels represent one of the most viable alternatives to petroleum-based fuel to meet transportation needs in the 21st century. The biofuel industry is in its infancy in Canada but shows considerable growth opportunity. The international interest in biofuels due to environmental and energy security concerns could result in a large and profitable export market for Canadian biofuel producers. Many industry participants are beginning to use biotechnology in their production processes to lower costs. Such use means they will be forced to contend with the unclear international regulation of trade in the products of biotechnology. Substantially different rules have been created by the Cartagena Protocol on Biosafety to the Convention on Biological Diversity, which governs only trade in biotechnology products, and the World Trade Organization, which governs trade in all goods. The inconsistencies of the regulatory situation create significant risks for biofuel producers, as their products may be blocked from important export markets.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.231
Teacher spread0.190 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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