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Record W1978557481 · doi:10.2750/arp.25.21

Eveluation of Burning Plant Residues and Farmers' Participation in International Cooperative Program for Resources Recycling System through Composting in Uttaradit of Northern Thailand

2006· article· en· W1978557481 on OpenAlexaff
Machito Mihara, Lalita Siriwattananon, Takashi Ueno, Rangsarit Srimuang

Bibliographic record

VenueJOURNAL OF RURAL PLANNING ASSOCIATION · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsAgricultureAdaptabilityNatural resourceCitizen journalismBusinessAgroforestryAgricultural scienceAgricultural economicsEnvironmental scienceEnvironmental protectionGeographyEconomicsEcologyPolitical science

Abstract

fetched live from OpenAlex

This report dealt with the changes in burning density and the characteristics of agricultural fields where the burning were conducted in Nam Pat district of Uttaradit province, Thailand. Also the contents of international cooperative program for natural resources recycling conducted by Japanese NGO were evaluated on the basis of participatory level. There was a tendency for the burning density to be gradually higher every year. Also, agricultural fields, where the burning was conducted, tended to be bounded on water resources or forest. Through the evaluation of farmers' participation, it was concluded that the deeper farmers' perception led to the higher farmers' participation, and directly it connected to farmers' adaptability for organic farming. For decreasing the frequency of the burning, composting is the one of farmers' alternative, which may contribute to sustainable agriculture.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.291
Teacher spread0.274 · 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 designObservational
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

Citations0
Published2006
Admission routes1
Has abstractyes

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