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Record W1969611852 · doi:10.1088/0960-1317/19/1/015010

The effect of thermal conductivity of the tool electrode in spark-assisted chemical engraving gravity-feed micro-drilling

2008· article· en· W1969611852 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Machining and Optimization Techniques
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEngravingMachiningElectrodeThermal conductivityDrillingSPARK (programming language)Electrical discharge machiningMaterials scienceThermalMechanical engineeringConductivityComposite materialMetallurgyEngineeringChemistryComputer science

Abstract

fetched live from OpenAlex

Spark-assisted chemical engraving (SACE) is a non-traditional micro-machining technology based on electrochemical discharge phenomena. In SACE gravity-feed micro-drilling, various parameters including the thermal properties of the tool electrode play a significant role in the process. Based on a series of experiments using tool electrodes with different thermal properties, the effect in SACE gravity-feed micro-drilling is discussed. It is demonstrated that machining with higher thermal conductivity tool electrodes results in faster machining during the discharge regime and slower machining during the hydrodynamic regime of SACE gravity-feed micro-drilling.

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)0.000
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 score0.019
Threshold uncertainty score0.469

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 head0.004
GPT teacher head0.186
Teacher spread0.182 · 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