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Record W1970607649 · doi:10.1002/jctb.3793

Influence of uric acid amendment on the in‐vessel process of composting composite food waste

2012· article· en· W1970607649 on OpenAlexafffund
Chunjiang An, Guohe Huang, Sheng Li, Hui Yu, Wei Sun, Peng Kuang

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Education, IndiaMinistry of Earth Sciences
KeywordsFood wasteAmendmentManureChicken manureEnvironmental scienceWaste managementGreen wasteFood scienceCompostPulp and paper industryChemistryAgronomyBiologyEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract BACKGROUND: The food waste produced in small cities, rural areas and small communities often coexists with agroindustrial waste, such as livestock and poultry manure, which include high levels of uric acid (UA). This study investigated the influence of UA on the composting of food waste in an in‐vessel system. RESULTS: Results showed that the performance of food waste composting was significantly different in systems with UA amendment and without UA amendment. Treatment with UA addition was the first to reach the thermophilic phase. More intensive mass reduction took place in the UA‐amended treatments at an early stage. The variations of pH and O 2 uptake were also correlated with the added UA. A decreasing trend in C/N ratio and a general increasing trend for NH $_{4}^{+}$ ‐N concentration were observed when UA was added. CONCLUSIONS: The overall effect of UA can be assumed to be the sum of a large number of individual events with different mechanisms. Appropriate strategies could be applied to adjust the composting process, mediating both positive and negative effects of the coexistence of food waste and UA as well as manure. The results from this study may have important implications for composting technologies used to treat food waste. Copyright © 2012 Society of Chemical Industry

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)0.001
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 score0.017
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.244
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Chemical Technology & BiotechnologySame topicComposting and Vermicomposting TechniquesFrench-language works237,207