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Record W3157798394

EXTRACTION AND CHARACTERIZATION OF FISH OIL FROM CHANNA STRAITA WASTE COLLECTED FROM ANANTAPURAM FISH MARKET

2020· article· en· W3157798394 on OpenAlexaboutno aff
Guldonahon Kabiljanovna Mahpieva, Furkat Mukhitdinovich Shamsiev, Nigora Davlyatovna Azizova, Abdukadir Gulyamovich Arzibekov, Kobiljon Komilovich Amanov, Khilola Erkinovna Turakulova

Bibliographic record

VenueJournal of Natural Remedies · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFisheries and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSteamingExtraction (chemistry)Fish <Actinopterygii>FisheryCrude oilBiologyToxicologyEnvironmental sciencePulp and paper industryFood scienceChemistryEngineeringChromatography
DOInot available

Abstract

fetched live from OpenAlex

Channa straita waste was collected from fish landings of Anantapuram, for a period between October 2013-September 2014. Since these species are landed only during certain corners of the year, specimens of uniform size from all three species were alone taken into consideration for the production of fish oil. The fish body oil was extracted from the tissues of Channa straita employing four different extraction methods, namely Bligh & Dyer, Modified Bligh & Dyer, Mcgill & Moffat and Direct Steaming. From the results it is proved that direct steaming method as the finest extraction process due to its winsome qualities such as higher yield, economic viability, less laborious and less time consumption. Analytical properties of the crude fish oil were evaluated separately for freshly prepared samples and for 30 days old samples which were stored in refrigerator at 0oC. These analytical values of the crude oil are well within the acceptable standard values for both fresh and stocked samples. It is important to note that the values for both fresh and 30 days old refrigerated samples did not having much variation.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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