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Record W6989240583

ẢNH HƯỞNG CỦA NHIỆT ĐỘ LÊN HÀM LƯỢNG B-CAROTENE TRÍCH TỪ DẦU GẤC, BÍ ĐỎ VÀ LÊ-KI-MA

2012· article· vi· W6989240583 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Languagevi
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSoutheast asiaNova scotiaQualitative analysisCentral asia
DOInot available

Abstract

fetched live from OpenAlex

Gấc, bí đỏ và lê-ki-ma là những loài được trồng phổ biến ở Việt Nam và chứa nhiều b-carotene. Kết quả cho thấy, hệ thống Soxhlet với dung môi là diethyl ether cho hiệu quả ly trích dầu gấc tối ưu so với phương pháp ngâm chiết với các dung môi hữu cơ khác. Phân tích hàm lượng b?carotene bằng phương pháp quang phổ cho kết quả đáng tin cậy. Hàm lượng b-carotene trong dầu gấc cao hơn hẳn trong bỉ đỏ và lê-ki-ma. Nhiệt độ đun nấu không những thúc đẩy rất nhanh sự phân hủy b-carotene có trong dầu gấc, bí đỏ và lê-ki-ma, giảm khoảng 50% sau khi đun sôi thịt trái bí đỏ trong 5 phút, mà còn làm giảm đáng kể hàm lượng protein hòa tan có trong bí đỏ, khoảng 14 lần sau khi đun sôi 5 phút.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0050.008
Open science0.0080.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1220.001

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 head0.360
GPT teacher head0.585
Teacher spread0.225 · 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; both teacher heads agree on what is shown here.

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
Published2012
Admission routes1
Has abstractyes

Explore more

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