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Record W2388210300

The present state of production and quality analysis of twin-shaft paddle aqua feed mixers in China

2012· article· en· W2388210300 on OpenAlexaboutno aff
GE Yi-jian

Bibliographic record

VenueFishery Modernization · 2012
Typearticle
Languageen
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsnot available
Fundersnot available
KeywordsPaddleMixing (physics)Production (economics)Quality (philosophy)ChinaEngineeringEnvironmental scienceMechanical engineeringGeographyPhysicsEconomics
DOInot available

Abstract

fetched live from OpenAlex

Based on summarizing working principle,distinguishing features and application of twin-shaft paddle aqua feed mixers,including a brief introduction of some latest models in Norway,Netherlands,Canada,Denmark and France,this study focused on the twin-shaft paddle aqua feed mixer product quality test results in the past 10 years.The production quality is much better than a few years ago in most manufactories,especially in Jiangsu Province,product quality of some backbone production enterprises is significantly better than manufactories in other provinces in China.Some performance parameters of twin-shaft paddle aqua feed mixers need to be more rational and scientific.Certain parameters such as retention rate should be set to segmentation value.The development tendency of twin-shaft paddle aqua feed mixer is to reduce mixing duration and energy consumption,enhance mixing uniformity and stability,expand the range of application and applicability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.213
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

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