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Record W2884201880 · doi:10.1002/fsn3.747

Determination of citric acid pretreatment effect on nutrient content, bioactive components, and total antioxidant capacity of dried sweet potato flour

2018· article· en· W2884201880 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFood Science & Nutrition · 2018
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsMcGill University
FundersJimma University
KeywordsChemistryFood scienceOrange (colour)AntioxidantProximateCitric acidPotato starchMoistureAntioxidant capacityStarchBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Orange flashed sweet potatoes are rich and inexpensive source of diet and antioxidants. The purpose of this study was to evaluate the effects of CA pretreatments and convective hot air drying temperature on proximate composition, bioactive components, and total antioxidant capacity of flour of five orange flashed sweet potato varieties. Moisture, protein, ether extract, ash, carbohydrate, fiber, β‐carotene, total phenolic compounds, and total antioxidant capacity in the dried flour samples were evaluated and reported in the range of 4.1–7.4%, 2.4–4.2%, 1.2–1.1.8%, 2.2–3.2%, 82.7–87.1%, 1.3–1.8%, 35.5–91.6 mg/100 g, 49.8–107.9 mg GAE /100 g, and 27.3–85.4%, respectively. The interaction effects of varieties, drying temperature, and CA concentration were significant ( p ˂ 0.05) except for fiber. Kulto and SPK 006/6/6 performed better for most of the parameters studied followed by SPK 00/06. For almost all varieties, samples dried at 55°C and after treated in 3% CA solution had the highest percentage in terms of proximate composition, bioactive components, and total antioxidant capacities.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
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 head0.028
GPT teacher head0.263
Teacher spread0.235 · 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