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Record W2953929464 · doi:10.1039/9781788016131-00001

Sustainability of Green Synthetic Processes and Procedures

2019· book-chapter· en· W2953929464 on OpenAlexaboutno aff
István T. Horváth, Edit Cséfalvay

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBiomass (ecology)Sustainable developmentRenewable energyEnvironmental economicsNatural resource economicsWaste managementEnvironmental scienceBusinessEngineeringEconomicsEcology

Abstract

fetched live from OpenAlex

Although the ecological footprint was perhaps the first green metric, the atom economy and E-factor have become the key metrics of green chemistry by providing the mass balance of chemical reactions and processes at the molecular level. Sustainability was poorly defined originally, since the key requisite to accurately forecast the needs of future generations remains difficult to pinpoint. Consequently, sustainability was replaced with suitability by many stake holders, as they had vested and/or conflicts of interests to label suitable developments sustainable. The sustainable development goals recently introduced by the United Nations seem to serve as a ‘roadmap to happiness’ instead of metrics. A simple and independent definition of sustainability was recently provided: Nature's resources, including energy, should be used at a rate at which they can be replaced naturally, and the generation of wastes cannot be faster than the rate of their remediation by Nature. The ethanol equivalent, the sustainability values of resource replacement and fate of waste, and the sustainability indicator have been recently defined to measure the sustainability of biomass-based carbon-chemicals and renewable energy. The production of ethylene, propylene, toluene, xylenes, styrene, and ethylene oxides cannot be sustainable due to the limited amount of bioethanol. The required volume of corn and the corresponding size of land are only enough to replace one sixth of fossil resources in the USA, EU, and China, and practically insufficient in Canada and the Russian Federation. Until the utilization of electricity becomes practical and economical in aviation, biomass-based liquid fuels are the sustainable alternative.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.463
Threshold uncertainty score0.999

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)0.0020.000

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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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
GenreOther

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

Citations3
Published2019
Admission routes1
Has abstractyes

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