Thermal Properties of Kabuli Type Chickpea
Bibliographic record
Abstract
Thermal properties namely thermal conductivity, specific heat and thermal diffusivity ofkabuli type chickpea (Cicer arietinum L.) were determined. Thermal conductivity of chickpea wasdetermined at temperatures ranging from 25C to 98C and moisture contents of 7 to 25% w.b. Itwas measured by the transient technique using the line heat source method assembled in a thermalconductivity probe. The thermal conductivity values obtained ranged from 0.1535 to 0.3257 Wm -1K-1.Specific heat was measured using an assembled calorimeter at moisture contents ranging from 9.86to 65.24% and the values obtained were between 1.3749 to 2.4802 kJ kg -1K-1. The specific heat wasalso measured using differential scanning calorimetry (DSC) at temperatures ranging from 30 to80C and moisture contents ranging from 9.86 to 65.24%. Specific heat values obtained by the DSCmethod ranged from 1.154 to 2.568 kJ kg -1K-1. The thermal diffusivity was calculated and the valuesranged from 9.11 X 10-8 to 25.05 X 10-8 m2 s-1. It was observed that the thermal conductivity andspecific heat of chickpea seed increased with increasing moisture content and temperature. Thermaldiffusivity increased with increase in moisture content and decreased with increase in temperature.Simple empirical models were developed to express thermal properties as a function of moisturecontent and temperature.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".