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Record W3140696830 · doi:10.1080/17597269.2021.1899363

Analysis of biogas production potential based on livestock dung availability: A case of household biogas plants in Nepal

2021· article· en· W3140696830 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

VenueBiofuels · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLivestockFodderBiogasMonsoonEnvironmental scienceAgroforestryCow dungAgronomyGeographyBiologyEcologyFertilizerForestry

Abstract

fetched live from OpenAlex

This paper presents an analysis of the potential for household-scale biogas production based on cattle and buffalo dung in three geographical regions of Nepal. A field survey was conducted in 240 livestock-holding households, and data of daily fresh dung yield were obtained from 210 livestock individuals classified into four categories: mature buffalo (>3 year), young buffalo (≤3 year), mature cattle (>3 year) and young cattle (≤3 year). The data were collected in three different seasons with varying temperature and humidity. The energy values of the dung were experimentally measured. The results showed that the average daily dung yield per livestock in the monsoon was higher than that of the other seasons, for all geographical regions, because of higher fodder availability. Despite the highest livestock number per household in the mountains as compared to the hills and lowlands, the net availability of dung in the mountains was only about 30% of that of other two regions due to lower availability of fodder. Fodder availability, livestock herding hours, quality of dung and seasonal variations were found to be important parameters in determining the net potential biogas production. Based on these findings, measures to increase biogas production from available dung are discussed and generalized.

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 score0.053
Threshold uncertainty score0.592

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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