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Record W3135945246 · doi:10.26656/fr.2017.5(2).520

Novel practice to produce safe and healthy dry fish using irradiated chitosan coating

2021· article· en· W3135945246 on OpenAlexaff
M.L. Rahman, Rajesh Barua, Ahmmed Jubayer, Jahid M. M. Islam, Abu Hena Mostofa Kamal, Motalebi Abas Ali, Md. Selim Hossain, Moshiur Rahaman, M.A. Hossain, Roksana Huque, Muhammad Attique Khan

Bibliographic record

VenueFood Research · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChitosanContaminationCoatingFungicideInfestationFish <Actinopterygii>ToxicologyDry weightFood scienceHorticultureBiologyChemistryPulp and paper industryEcologyFishery

Abstract

fetched live from OpenAlex

In Bangladesh, dry fishes are mostly produced by drying in an open environment under sunlight, and so the producers are forced to use insecticides and fungicides to prevent microbial and blowfly infestation. That is why dry fishes are often contaminated with residual insecticides and fungicides, which cause a severe threat to human health. In this experiment, gamma radiation treated chitosan solution was used while drying the fishes, and the effect was evaluated. Experimental results suggested that chitosan coating did not hinder the drying process but improved the quality of the produces. Chitosan coating was found as a repellant of blowflies as well. Besides, it also prevented microbial contamination. The nutritional value of the produced dry fishes was examined and found very satisfactory. Overall results suggested that the application of irradiated chitosan can be a very suitable and cost-effective way to produce safe and healthy dry fishes.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0020.000

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 head0.171
GPT teacher head0.383
Teacher spread0.212 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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