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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 OpenAlexaff
Devinder Singh, Giovanna Gonzales‐Calienes

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.014

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

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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2020
Admission routes1
Has abstractyes

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