MétaCan
Menu
Back to cohort

INTERPRETATION OF THE FORCE–DEFORMATION CURVES OF COOKED RED LENTILS (<i>LENS CULINARIS</i>)

2009· article· en· W2049380049 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Texture Studies · 2009
Typearticle
Languageen
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsCanadian International Grains InstituteUniversity of Manitoba
Fundersnot available
KeywordsDeformation (meteorology)Inflection pointTexture (cosmology)Plateau (mathematics)MathematicsFood scienceMineralogyMaterials scienceGeometryArtificial intelligenceGeologyChemistryComposite materialComputer scienceMathematical analysisImage (mathematics)

Abstract

fetched live from OpenAlex

ABSTRACT The effect of cooking time on the textural properties of red lentils was determined using an Instron universal testing machine equipped with an Ottawa texture cell. A sigmoid‐shaped force–deformation curve was observed for all samples. As cooking time increased, texture changes, in terms of undercooked and optimally cooked, were identified by changes in slope and plateau force values of the force–deformation curves. At short cooking times, the samples were undercooked, and slope and plateau force values were high. At prolonged cooking times, slope and plateau force values decreased to a certain point and became independent of cooking time as values leveled off. However, significant textural changes as determined with sensory methods continued. Cooking time affected the location of the inflection point on the force–deformation curve. Deformation at inflection was a parameter that successfully determined textural differences between cooked samples and overcooked samples. Force–deformation curves can describe cooking quality of red lentils. PRACTICAL APPLICATIONS There is little information available on the instrumental methods used to measure the texture of red lentils despite the fact that red lentils account for the majority of world lentil production and trade. Thus, there is a need to demonstrate how the force–deformation curves resulting from the instrumental measurement of red lentil texture are affected by cooking. A detailed interpretation of a force–deformation curve would allow for investigation of the effects of biochemical differences in red lentils because of genotype, agronomic practices and postharvest handling on the cooking quality. This work used an Instron universal testing machine equipped with an Ottawa texture cell to obtain force–deformation curves that were interpreted and used to explain the effects of cooking on the textural properties of red lentils.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.173

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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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