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Record W2069426982 · doi:10.5539/apr.v1n2p68

Study on the Laser Hybrid Cladding Technology on the Surface of Copper Substrate

2009· article· en· W2069426982 on OpenAlexvenueno aff
Fudong Zhu, Yunshan Wang

Bibliographic record

VenueApplied Physics Research · 2009
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsnot available
Fundersnot available
KeywordsCladding (metalworking)Materials scienceLaserSubstrate (aquarium)Composite materialMetallurgyOpticsPhysics

Abstract

fetched live from OpenAlex

To enhance the staying quality of the surface of the copperplate, the laser hybrid cladding technology can be used toclad Ni-Cr alloy on the surface of the copperplate. By the traditional laser cladding technology, it is hard to directlyform good coat on the surface of the copperplate. In the article, the coat is made on the surface of the copperplate by thelaser hybrid cladding technology, and the staying quality tests are made for samples by several methods, and themicro-hardness and the staying quality of the coat are far higher than the cooper substrate, and coat has good roughnessof surface. And the test result indicates that the method adopting the laser hybrid cladding technology can prepare thealloy coat on the surface of the deep copperplate.

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)0.001
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 score0.454
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.070
GPT teacher head0.316
Teacher spread0.246 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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