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Record W1984215419 · doi:10.1088/0957-0233/16/5/018

Prediction of moisture content of alfalfa using density-independent functions of microwave dielectric properties

2005· article· en· W1984215419 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

VenueMeasurement Science and Technology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWater contentMicrowaveMaterials scienceDielectricBulk densityRange (aeronautics)MoistureComposite materialSoil scienceAnalytical Chemistry (journal)Environmental scienceOptoelectronicsSoil waterComputer scienceChemistryTelecommunicationsGeotechnical engineeringEnvironmental chemistryGeology

Abstract

fetched live from OpenAlex

The use of density-independent functions of the dielectric properties of chopped alfalfa, calculated from microwave reflection coefficients from 300 MHz to 18 GHz, was studied for determining moisture content in the range from 12% to 73%, wet basis, at bulk densities from 0.139 to 0.716 g cm−3 at 20 °C. Prediction of moisture content with worst-case relative errors of about 3% or less over the range from 20% to 73% confirmed promising prospects for use of such density-independent functions for reliable moisture measurement for important plant materials.

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)0.001
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 score0.034
Threshold uncertainty score0.153

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.123
GPT teacher head0.210
Teacher spread0.087 · 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