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Impact of Initial pH and Linoleic Acid (C18:2) on Hydrogen Production by a Mesophilic Anaerobic Mixed Culture

2008· article· en· W1964976264 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsUniversity of WindsorWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryPropionateLinoleic acidMesophileButyrateAnaerobic exerciseHydrogen productionHydrogenEthanolYield (engineering)ButanolChromatographyNuclear chemistryBiochemistryFood scienceFatty acidOrganic chemistryFermentationBacteriaBiology

Abstract

fetched live from OpenAlex

Hydrogen production from glucose using a mixed anaerobic culture was assessed under batch conditions by adjusting the initial pH and adding linoleic acid (LA). At an initial pH of 5.0, hydrogen (1.9molH2mol−1 glucose) was detected after the first glucose injection in the controls (no LA added). At the latter initial pH and in cultures fed 2,000mgl−1 LA, the yield reached a maximum of 2.4molH2mol−1 glucose when glucose was injected again. Hydrogen was detected after the second glucose injection in cultures with the initial pH adjusted to 5.0 and 6.0. In cultures receiving LA and adjusted to pH 7.6, the hydrogen yield reached 1.4molH2mol−1 glucose when glucose was injected again. Acetate, propionate, and butyrate were detected under all conditions; however, the quantities were variable and dependent on the conditions examined. In comparison to the amount of volatile fatty acids produced, relatively low quantities of alcohols (ethanol, i-propanol, n-butanol, and i-butanol) were detected during the initial lag phase of 96to120h.

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 score0.112
Threshold uncertainty score0.614

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 head0.006
GPT teacher head0.203
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