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Record W1980448872 · doi:10.1109/icacte.2010.5579244

Lift-off type Pu'er tea fermentation pot's design and automatic control research

2010· article· en· W1980448872 on OpenAlexaboutno aff
MA Zhen-gang, Yunzhan Huang, Dapeng Liu, Hongjie Zhou, Tongqiang Xiong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsFermentationStandardizationHumidityProcess engineeringComputer scienceEnvironmental sciencePulp and paper industryFood scienceEngineeringChemistryPhysics

Abstract

fetched live from OpenAlex

The traditional Pu'er tea fermentation is uses the man-power to moisten naturally in the workshop piles the fermentation, this fermentation way cannot guarantee that in the Pu'er tea fermentative process the humidity uniformity, produces the workshop and the Fermentation plant to the Pu'er tea carries on the design and the research, the microorganism technology, the machine-finishing technology and the electric control technology merges into one organic whole, causes the Pu'er tea the production standardization, and has the scientific nature. The Pu'er tea fermented the clear purification workshop to unify the technology which the tradition fermented, used modernized the examination control technology and the equipment, by humidity sensor, PLC master control equipment, computer constitutions and so on processing system, Canadian wet equipment and supervisory system. This article through constructs the Pu'er tea to ferment the clear purification workshop, carries on the control to the workshop ambient humidity, causes the Pu'er tea to be stable in fermentative process environment, and has carried on the production testing under this kind of environment, obtains the experimental correlation data and carries on processing, discovers the Pu'er tea fermentation humidity from the tentative data to form the influence to the Pu'er tea quality some rules, ferments the formalization production for the Pu'er tea to provide the corresponding scientific parameter.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.283

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 head0.028
GPT teacher head0.304
Teacher spread0.275 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2010
Admission routes1
Has abstractyes

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