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Record W3097014650 · doi:10.1007/978-981-15-7518-1_11

Liquid Biofuels from Algae

2020· book-chapter· en· W3097014650 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

VenueALGAE · 2020
Typebook-chapter
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsBiofuelFossil fuelBiomass (ecology)Arable landEnvironmental scienceAlgaeWaste managementBiochemical engineeringBiotechnologyEngineeringEcologyBiologyAgriculture

Abstract

fetched live from OpenAlex

Extensive uses of fossil fuels are posing several threats to the environment as well as human health. They have been used in such a way that in coming few decades, the finite sources of fossil fuels will be completely exhausted. Algae are one of the most primitive microorganisms on the Earth. They are small photosynthetic organisms that have an ability to completely replace the need of conventional fossil fuel for energy demand. They are robust microorganisms and can be grown in photo-bioreactors, open ponds, sewage or industrial waste without the need of arable land. Microalgal biomass can be converted to variety of biofuels via biochemical and thermochemical methods, they can also be used for the production of high value nutraceuticals at industrial scale. The present chapter deals with the various conversion technologies of algal biomass to biofuel, resource requirements, research gaps and operational costs associated with it.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.829
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.013

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 head0.219
Teacher spread0.197 · 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