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On Checking the Rising Global Food Prices Due to Bio-Fuels Using Solar Energy

2009· article· en· W2019604524 on OpenAlexaff
Anand M. Sharan

Bibliographic record

VenueEnergy & Environment · 2009
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFossil fuelSolar energyEnvironmental scienceNatural resource economicsGlobal warmingCombustionProcess (computing)Agricultural engineeringWaste managementClimate changeEconomicsEngineeringComputer scienceChemistryEcologyBiology

Abstract

fetched live from OpenAlex

This paper deals with the pressing current global problem of the sudden price rise in food grains all over the world which is unprecedented. This has mainly arisen from use of food crops such as corn, sugar cane etc as bio-fuels. This paper suggests use of solar energy which is not only widely abundant, it also does not cause global warming, a harmful effect due to the combustion of fuels whether bio-fuels or fossil. This paper also suggests use of other forms of vehicles which are far more economical to use. In addition, this paper shows results of an efficient process of conversion of solar energy into useful forms; this process is the solar tracking process. If used world wide, one would obtain about 36% more energy whose cost is touching the sky these days.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score1.000

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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.

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
Published2009
Admission routes1
Has abstractyes

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