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Record W2349747127

Effect of different fillers on aerobic composting of dewatered sludge

2013· article· en· W2349747127 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.

Bibliographic record

VenueDongbei Nongye Daxue xuebao · 2013
Typearticle
Languageen
FieldEngineering
TopicPolymer-Based Agricultural Enhancements
Canadian institutionsScience North
Fundersnot available
KeywordsHuskFly ashCompostStrawSewage sludgeWaste managementEnvironmental scienceFertilizerPulp and paper industrySoil conditionerFiller (materials)AgronomySewageEnvironmental engineeringMaterials scienceSoil waterBiologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

The method of aerobic windrow composting was used in this experiment. It was studied that effects of straw and rice husk as bulking agents and conditioner, zeolite and fly ash as adjusting agent on sewage sludge composting, in order to provide the basis for reasonable land utilization of sludge. The test results showed that: the straw treatment groups all reached the standard of harmless and decomposed, but rice husk treatment groups did not reach the standard; fly ash treatments and zeolite treatments were no differences. Under the condition of straw as bulking agents and conditioner,fly ash or zeolite as adjusting agent, sludge was composted. Fertilizer index after composting had reached the national standard for organic fertilizer. There were more development prospects with waste straw and fly ash as the sludge compost filler.

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 score0.009
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.192
Teacher spread0.188 · 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