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Record W2051973903 · doi:10.1089/ind.2007.3.133

Agriculture and forestry for energy, chemicals, and materials: The road forward

2007· article· en· W2051973903 on OpenAlex
R. W. F. Hardy, A. Eaglesham, Anthony M. Shelton

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndustrial Biotechnology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsPlant Biotechnology Institute
Fundersnot available
KeywordsAgricultureBusinessNatural resource economicsCommodityBiomass (ecology)Chemical industryPetroleumAgricultural economicsEconomicsEnvironmental scienceFinanceEnvironmental engineering

Abstract

fetched live from OpenAlex

The document calls for a national mobilization, by academe, government, and industry, to expeditiously move the United States economy from mainly petroleum-based industry to a more sustainable biological- and petroleum-based industry, calling for 100-plus billion gallons annually of transportation fuel and value-added chemicals and materials produced from biomass. The plant-based agricultural and forestry traditional commodity and new value-added markets can be simultaneously served without long-term negative impacts of one on the other, provided there is major biosource and bioprocess innovation for biobased industrial products. The benefits will be far-reaching, from self-sufficiency in transportation fuel to more sustainable industries, revitalization of rural economies, and improved balance of payments, to mitigation of environmental problems. Targets for biosources, processes, and costs are proposed as well as an integrated structure for success by 2025.

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.

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 score0.608
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.214
Teacher spread0.192 · 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