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Record W48821728 · doi:10.53846/goediss-1745

Methodische Untersuchungen zum Einsatz der Nahinfrarot-Spektroskopie (NIRS) zur Qualitätsbeurteilung von High-Oleic-Sonnenblumen

2007· dissertation· de· W48821728 on OpenAlexfundno aff
Christian R. Moschner

Bibliographic record

Venuenot available
Typedissertation
Languagede
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsnot available
FundersUniversidade Federal de Ouro PretoRheinische Friedrich-Wilhelms-Universität BonnKillam Trusts
KeywordsAcheneSunflowerSunflower oilYield (engineering)ChemistryFood scienceOleic acidMathematicsEnvironmental scienceHorticultureMaterials scienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

To determine the different quality parameters of high-oleic (HO) sunflower achenes, reliable analytical methods are necessary in order to achieve optimal yield and value for both, the food and non food area. It is therefore recommended to use near-infrared spectroscopy (NIRS), which allows the simultaneous determination of several parameters in a time and cost-saving way. The objective of this investigation is to develop, optimise and assess efficient and robust near-infrared calibrations to estimate the quality parameters (content of moisture, oil, protein, fatty acids and free fatty acids) of ground and intact high oleic sunflower achenes.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.175
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0470.004

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 head0.019
GPT teacher head0.353
Teacher spread0.334 · 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
GenreOther

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

Citations3
Published2007
Admission routes1
Has abstractyes

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