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Record W2883749828 · doi:10.5376/ijh.2018.08.0015

Economic and Environmental Considerations in Collection and Processing of Winged Termites as Food in Tamil Nadu, India

2018· article· en· W2883749828 on OpenAlexvenueno aff
C. Sekhar, P. Pradeep Kumar, A. Vidhyavathi, S. Sivakumar

Bibliographic record

VenueInternational Journal of Horticulture · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsTamilAgroforestryGeographyBiologyArt

Abstract

fetched live from OpenAlex

There are several species under the head “Winged Termites”. In the entomologists’ Point of view, they are asset destroying agents and in the biological sense, they are friends of farmers and in the consumption point of view, they are highly nutritious and capable of curing certain contagious diseases. Among the many species of winged termites, few species are widely collected by tribes and the rural people during the season and they process and value add the termites along with certain ingredients and make a tasty and enjoyable food products. The popular species among the winged termite is Odontotermes formosanus which is a rich source of protein, thus forming an important diet for pregnant women and children in the rural settings. Though many south Indian tribes are engaged in the collection process, other rural communities are also greatly involved in collecting, preserving and value adding the produce of termites. This paper presents the method of collection, preservation and value addition methods and distribution for consumption both in the rural and semi urban environments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.238
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2018
Admission routes1
Has abstractyes

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