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Record W2066282003 · doi:10.5539/mas.v3n8p32

Production of Bio-ethanol from Sugar Molasses Using Saccharomyces Cerevisiae

2009· article· en· W2066282003 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2009
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
Fundersnot available
KeywordsSugarFermentationEthanolEthanol fuelSubstrate (aquarium)Yield (engineering)Saccharomyces cerevisiaeBiomass (ecology)ChemistryFood scienceEthanol fermentationBiochemistryYeastBiologyMaterials scienceAgronomy

Abstract

fetched live from OpenAlex

Saccharomyces cerevisiae is the cheapest strain available for the conversion of biomass substrate. In the present study, it is used for bio-ethanol production from sugar molasses. The influencing parameters that affect the production of bio-ethanol from sugar molasses are optimized. The optimal values of the parameters such as temperature, pH, substrate concentration, enzyme concentration and fermentation period are found to be 35°C, 4.0, 300 gm/l, 2 gm/l and 72 h respectively. Under this optimum operating condition the maximum of 53% bio-ethanol yield is achieved. The rate of formation of bio-ethanol is found to be well fitted with Michael-Menten equation and the rate constants such as Vmax and Km are found to be 0.71 mol/l sec and 81.63 mol/l respectively.

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 categoriesnone
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 score0.079
Threshold uncertainty score0.422

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 head0.020
GPT teacher head0.230
Teacher spread0.211 · 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