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Record W4366981676 · doi:10.1016/j.bej.2023.108954

Biomethane potential of wine lees from mesophilic anaerobic digestion

2023· article· en· W4366981676 on OpenAlex
Marco Chiappero, Franco Berruti, Silvia Fiore

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.

Bibliographic record

VenueBiochemical Engineering Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsWestern University
Fundersnot available
KeywordsLeesBiogasMesophileAnaerobic digestionMethanogenesisChemistryPulp and paper industryWineFood scienceBiodegradationMethaneWaste managementBiologyOrganic chemistryBacteriaEngineering

Abstract

fetched live from OpenAlex

Wine lees (WL) are undervalued residues from the wine-making process. Anaerobic digestion (AD) of WL is highly challenging due to the acidic pH and high content of readily biodegradable compounds. This study investigated the biomethane potential (BMP) of 3 WL samples through mesophilic batch tests fed with 2–3 % total solids. The influence of wood-based biochar (BC), considering 2 different BCs and doses (3 and 10 g L−1), was also assessed. BMP values up to 1.257 Nm3 kgVS−1 and 92–96 % soluble COD removal were recorded. However, the inhibition of methanogenesis was observed due to organic acids accumulation exceeding 21–24 g L−1. BC addition didn’t improve biomethane production in the considered experimental conditions. This study proved that WL is a highly attractive AD substrate, considering its high biodegradability and availability throughout the year, although the process must be carefully operated.

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 score0.018
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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