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Record W2409011196 · doi:10.6000/1927-5129.2016.12.35

Physico-Chemical Analysis and Composition of Camel Milk of Bangladesh

2016· article· en· W2409011196 on OpenAlexvenueno aff
Nilufar Nahar, Waliul I. Khan, Mohammad Shoeb

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Diversity and Health Studies
Canadian institutionsnot available
FundersUppsala Universitet
KeywordsChemistryFood scienceSaponification valueSaponificationBehenic acidCamel milkLactoseCitric acidCaseinOleic acidChromatographyComposition (language)Fatty acidIodine valuePalmitic acidBiochemistry

Abstract

fetched live from OpenAlex

Camel farming is increasing in Bangladesh but the nutritious value of the produced milk has not been studied in this geological location. The milk was coagulated by citric acid and the coagulated solid i.e. the casein (7%) and pure serum (14%) were obtained. Fat content was determined by extracting casein and the aqueous serum, separately with n-hexane and found 2.59% and 5.79%, respectively. The fatty acids in the fat from casein and serum were made into their methyl ester by saponification followed by esterification and analyzed by GC-FID. Palmitoleic, oleic and linoleic acids were predominant fatty acids found in the analyzed samples while stearic, arachidic, behenic and myristic acids were present as minor acids. Water, ash, nitrogen and lactose contents in the milk were 84%, 0.88%, 1.62% and 9.32%, respectively. The presence of vitamin B1, B2 and B6 were estimated by UV-VIS spectrophotometer and found 388, 64 and 116 ppm, respectively.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.025
GPT teacher head0.238
Teacher spread0.213 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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