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Record W2085659662 · doi:10.1080/10942910601137482

Thermal Properties of Sweet Potato with its Moisture Content and Temperature

2007· article· en· W2085659662 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

VenueInternational Journal of Food Properties · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsThermal diffusivityWater contentThermal conductivityThermalAtmospheric temperature rangeMaterials scienceSpecific heatMoistureThermodynamicsComposite materialPhysics

Abstract

fetched live from OpenAlex

Thermal properties of sweet potato were experimentally determined and modeled as a function of temperature and moisture content. The purpose is to develop empirical correlations that could predict thermal properties during sweet potato processing. Thermal conductivity from the study was 0.49 ± 0.038 Wm−1K−1 (mean ± s.d.), thermal diffusivity was 1.2 × 10−7 ± 9.05 × 10−9 m2s−1, specific heat was 3660 ± 477.4 Jkg−1K−1, and density was 1212 ± 73.5 kgm−3. All properties were determined within temperature range of 20 to 60°C and moisture content range of 0.45 to 0.75 w.b. Prediction models for the thermal properties of sweet potato were developed as a function of product temperature and moisture content with experimental data from this study. Mechanistic models were also developed for thermophysical properties of sweet potato using major food components of the product. Developed models were all presented and compared.

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 score0.119

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 head0.056
GPT teacher head0.217
Teacher spread0.160 · 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