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A geography‐based critique of new <scp>US</scp> biofuels regulations

2011· article· en· W2132523108 on OpenAlex

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

VenueGCB Bioenergy · 2011
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsBiofuelGreenhouse gasCorn ethanolBiomass (ecology)GasolineRenewable energyEnvironmental scienceBioenergyEthanol fuelRenewable fuelsLife-cycle assessmentProduction (economics)Renewable resourceNatural resource economicsAgricultural engineeringAgronomyWaste managementEngineeringEconomicsEcologyBiology

Abstract

fetched live from OpenAlex

Abstract The new renewable fuels standard ( RFS 2) aims to distinguish corn‐ethanol that achieves a 20% reduction in greenhouse gas ( GHG ) emissions compared with gasoline. Field data from Kim et al . (2009) and from our own study suggest that geographic variability in the GHG emissions arising from corn production casts considerable doubt on the approach used in the RFS 2 to measure compliance with the 20% target. If regulators wish to require compliance of fuels with specific GHG emission reduction thresholds, then data from growing biomass should be disaggregated to a level that captures the level of variability in grain corn production and the application of life cycle assessment to biofuels should be modified to capture this variability.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.582

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 integrity0.0000.000
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 head0.019
GPT teacher head0.210
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