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Record W4366715208 · doi:10.31399/asm.hb.v24a.a0006952

Nanoindentation Hardness, Strain-Rate Sensitivity, and Corrosion Response of Additively Manufactured Metals

2023· book-chapter· en· W4366715208 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.

Bibliographic record

VenueASM International eBooks · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNanoindentationMaterials scienceStrain rateCorrosionIndentationMetallurgySensitivity (control systems)Strain (injury)Composite materialElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract This article provides a detailed discussion on nanoindentation hardness, high-strain-rate behavior and strain-rate sensitivity, and corrosion response of additively manufactured (AM) metals. It summarizes the most commonly used AM alloys for applications in harsh environments and their respective corrosion responses in various service environments. It also provides several case studies on location-dependent properties, microstructural evolution, and indentation strain-rate sensitivity of various additively manufactured alloys.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.627
Threshold uncertainty score1.000

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 head0.020
GPT teacher head0.231
Teacher spread0.210 · 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