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Record W2329900296 · doi:10.1021/ie403354k

Pyrolysis Byproducts as Feedstocks for Fermentative Biofuel Production: An Evaluation of Inhibitory Compounds through a Synthetic Aqueous Phase

2013· article· en· W2329900296 on OpenAlexaff
Karen Schwab, Jeffery A. Wood, Lars Rehmann

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2013
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsWestern University
Fundersnot available
KeywordsPyrolysisBiofuelChemistryAqueous solutionProduction (economics)Phase (matter)Organic chemistryAqueous two-phase systemBiochemical engineeringPulp and paper industryBiotechnologyEconomicsBiology

Abstract

fetched live from OpenAlex

In this work, the viability of using aqueous-phase sugars derived from the pyrolysis of lignocellulosic biomass was analyzed using high-throughput screening in microtiter plates. To standardize results, a synthetic aqueous phase of pyrolytic bio-oil was constructed based on typical constituents and composition ranges and then used to determine the fermentation viability of Saccharomyces cerevisiae . The effects of inhibitory compounds in pyrolytic bio-oil were assessed by fitting measured growth kinetics to the model of Baranyi and Roberts ( Int. J. Food Microbiol. 1994, 23, 277), specifically on the fitted growth rates, initial microorganism adaptation, and maximum biomass densities. It was found that even a dilution to approximately 10% of the hypothetical inhibitor concentration in aqueous bio-oil was significantly inhibitory to growth, although the presence of additional sugars was able to moderate this impact slightly. The high-throughput screening used in this work allowed for the rapid measurement of a variety of inhibitors at different concentrations, as well as inhibitory mixtures.

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)0.001
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.368
Teacher spread0.248 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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