MétaCan
Menu
Back to cohort
Record W2148391344 · doi:10.24908/pceea.v0i0.3574

Enhancing a Junior Level Materials Lab with SEM Iimages

2011· article· en· W2148391344 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Selection and Properties
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCharpy impact testAlloyScanning electron microscopeContext (archaeology)Materials scienceMetallurgyFracture (geology)Scale (ratio)AluminiumComposite materialMicrostructurePhysicsGeology

Abstract

fetched live from OpenAlex

Lab courses can enhance a student's communicationskills, provide opportunities to practice team work, and raise self-confidence early in their university experience, as well as impart valuable technical knowledge. Students ran impact Charpy tests on alloy steel 1045, and aluminum alloy 6061 as a function of temperature, and then analyzed and investigated by unaided eye the fracture surface in the two alloys at the macro-scale level. In this paper, micro-scale level investigation by the scanning electron microscopy (SEM) images introduced for the first time in this context to enhanced junior level materials lab. Keywords: Students: SEM images: alloy steel 1045; aluminum alloy 6061; fracture surface

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)0.001
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 score0.028
Threshold uncertainty score0.980

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)0.0010.000

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 head0.015
GPT teacher head0.186
Teacher spread0.171 · 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