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Record W2145900245 · doi:10.5539/jas.v1n2p101

A Microcontroller-Based Monitoring System for Batch Tea Dryer

2009· article· en· W2145900245 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2009
Typearticle
Languageen
FieldComputer Science
TopicFuzzy Logic and Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsData loggerMicrocontrollerMoistureProcess (computing)Water contentController (irrigation)Environmental scienceProcess engineeringComputer hardwareComputer scienceEngineeringMaterials scienceOperating systemComposite material

Abstract

fetched live from OpenAlex

This paper presents an automated tea dryer system based on programmable controller which controls moisture contentof the tea leaves and temperature of the chamber in different stages of drying. Several techniques were used for teadrying systems according to the tea genres. The batch tea dryer is designed with 6 to 8 trays. The temperature above thetrays is controlled between 50ºC and 100ºC. Moreover, the moisture content of the tea leaves declined from around 68%to approximately under 3%. In addition, the temperature of the leaves increased from a little less than 30ºC to 80ºC. Amicrocontroller as the main processor was deployed to process received data from sensors and also it provides controlsignals. Thus, this system equipped a data logger memory to record data during drying process. The analyses of dryerproducts shown the feasibility of using propose system for batch tea drying.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.456

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 communication0.0000.001
Open science0.0020.000
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 head0.010
GPT teacher head0.226
Teacher spread0.215 · 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