MétaCan
Menu
Back to cohort
Record W6981496716

Energy and Greenhouse Gas Impacts of Biofuels: A Framework for Analysis

2008· article· en· W6981496716 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2008
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
FundersNatural Resources CanadaNational Science Foundation
KeywordsGreenhouse gasClimate changeResource (disambiguation)Energy balanceEnergy (signal processing)Global warmingRange (aeronautics)Energy consumptionEnvironmental impact of the energy industry
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we review some of the basic energy balance and climate change impact issues associated with biofuels. For both the basic energy and greenhouse gas balances of producing and using a range of fuels, and for the increasingly debated and important issues of nongreenhouse gas impacts such as land, fertilizer, and water use, we conclude that an improved framework for the analysis and evaluation of biofuels is needed. These new methodologies and data sets are needed on both physical and socioeconomic aspects of the life-cycle of biofuels. We detail some of components that could be used to build this methodology and highlight key areas for future research. We look at the history and potential impacts of building the resource base for biofuel research, as well as at some of the land-use and socioeconomic impacts of different feedstock-to-fuel pathways.

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)0.009
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.016
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0060.006
Science and technology studies0.0020.008
Scholarly communication0.0090.010
Open science0.0030.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.246
Teacher spread0.227 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueeScholarship (California Digital Library)Same topicChildren's Physical and Motor DevelopmentFrench-language works237,207