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Record W2357662718

Practice and Exploration of Improving the Application Efficiency of College Large-scale Instruments and Equipments

2014· article· en· W2357662718 on OpenAlex
YU Jian-cha

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

VenueResearch and Exploration in Laboratory · 2014
Typearticle
Languageen
FieldEngineering
TopicExtenics and Innovation Methods
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsStandardizationProcess (computing)Diversification (marketing strategy)Scale (ratio)Engineering managementComputer scienceJoint (building)Resource (disambiguation)Work (physics)Process managementKnowledge managementEngineeringOperations managementBusinessMarketingMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

For the problem of low use efficiency of college large instruments,the advanced pattern of instrument whole process management should be applied. The basic strategy of four in oneis beneficial to improve the whole process standardization,resource plat formulization,assess diversification,and college and enterprise joint of use. Then the efficiency of large instruments should be put forward. The four in onestrategy contains all people participation,all process management,resource share,college and enterprise joint. Excellent practical achievements show that basic strategies are scientific and feasible,it provides references for the management work of other colleges in large instruments management.

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)0.003
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.000
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 head0.039
GPT teacher head0.347
Teacher spread0.308 · 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