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Record W2970549273 · doi:10.3390/pr7090576

Effect of Hydrothermal Pretreatment on Volatile Fatty Acids Production from Source-Separated Organics

2019· article· en· W2970549273 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

VenueProcesses · 2019
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsGreenfield Research (Canada)Toronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Water Consortium
KeywordsChemistryHydrothermal circulationMineralization (soil science)Yield (engineering)Raw materialChemical oxygen demandSolubilizationFood scienceEnvironmental chemistryNitrogenBiochemistryOrganic chemistryWaste managementChemical engineering

Abstract

fetched live from OpenAlex

The current study investigates the effect of hydrothermal pretreatment (HTP) on acidification of source-separated organics (SSO) in terms of volatile fatty acids (VFAs) production and solubilization. Temperature and retention time for HTP of SSO ranged from 150 to 240 °C and 5 to 30 min, respectively. The soluble substance after hydrothermal pretreatment initially increased, reaching its peak at 210 °C and then declined gradually. The highest overall chemical oxygen demand (COD) solubilization of 63% was observed at “210 °C-20 min” compared to 17% for raw SSO. The highest VFAs yield of 1536 mg VFAs/g VSS added was observed at “210 °C-20 min” compared to 768 mg VFAs/g VSS for raw SSO. Intensification of hydrothermal pretreatment temperature beyond 210 °C resulted in the mineralization of the organics and adversely affected the process.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.436

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 head0.004
GPT teacher head0.205
Teacher spread0.202 · 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