MétaCan
Menu
Back to cohort

Feasibility study of resistance spot welding of dissimilar Al/Mg combinations with Ni based interlayers

2013· article· en· W2101180868 on OpenAlexaff
Pavlo Penner, Liang Liu, A.P. Gerlich, Y. Zhou

Bibliographic record

VenueScience and Technology of Welding & Joining · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceSpot weldingWeldingMetallurgyMicrostructureAluminiumNickelComposite materialShear strength (soil)

Abstract

fetched live from OpenAlex

Microstructure and mechanical properties of the dissimilar aluminium–magnesium resistance spot welds made with gold coated and bare nickel interlayers are investigated. Welds were made with different welding currents in a range from 16 to 24 kA with a fixed welding time of five cycles. No joints were achieved with a bare nickel interlayer; after welding, specimens were separated without applying any force. Addition of gold coating on nickel surface greatly contributed to the metallurgical bonding at the interfaces and welds easily met requirements of AWS D17·2 standard. Average lap shear strength reached 90% of similar AZ-31B spot weld strength. Fusion nugget size, interfacial microstructure and fracture surface morphology of the welds were analysed.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.251
Teacher spread0.240 · 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 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

Citations69
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueScience and Technology of Welding & JoiningSame topicAdvanced Welding Techniques AnalysisFrench-language works237,207