MétaCan
Menu
Back to cohort

YARD WASTE COMPOSTING AS A VIABLE COST REDUCTION PROCESS

2022· article· es· W4292787555 on OpenAlexaboutno aff
Paula von Randow Cardoso, Arthur Couto Neves, Marcos Paulo Gomes Mol

Bibliographic record

VenueRevista AIDIS de Ingeniería y Ciencias Ambientales Investigación desarrollo y práctica · 2022
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsYardContext (archaeology)Municipal solid wasteWaste managementBusinessGreen wasteEnvironmental scienceEngineeringCompostGeography

Abstract

fetched live from OpenAlex

Yard waste consist of garden waste, generated by public parks and private gardens routine maintenance such as grass clippings, leaves from deciduous trees, flowers, fallen fruits, branches, twigs and logs and its composition vary greatly depending on the original location due to climate and other environmental conditions. Yard waste may represent a problem to Municipal Solid Waste Management Programs due to its large volume thus, it is necessary to incentivize local composting programs. In this study we show a brief disposal cost estimation from different cities from United States of America and Canada and we discuss how this biowaste can be managed in order to reduce costs with storage, transportation and disposal fees, encouraging the utilization of the final product as a soil amendment, stimulating and reinforcing the circular economy concept. The composted yard waste may not substitute the use of commercial products but it can reduce the cost of acquisition of this soil conditioner as well costs waste management. Update in environmental public policies is essential to foment sustainable economy in this context.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
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 score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.285
Teacher spread0.257 · 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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRevista AIDIS de Ingeniería y Ciencias Ambientales Investigación desarrollo y prácticaSame topicComposting and Vermicomposting TechniquesFrench-language works237,207