EXTRACTION AND CHARACTERIZATION OF FISH OIL FROM CHANNA STRAITA WASTE COLLECTED FROM ANANTAPURAM FISH MARKET
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".