MétaCan
Menu
Back to cohort
Record W4385965005 · doi:10.1039/d3mh00885a

Erosion-resistant materials demonstrate low interfacial toughness with ice and superior durability

2023· article· en· W4385965005 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

VenueMaterials Horizons · 2023
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersMinistère de la Défense NationaleCanada Foundation for Innovation
KeywordsMaterials scienceToughnessDurabilityComposite materialAbrasion (mechanical)CeramicErosionIcingCoatingGeology

Abstract

fetched live from OpenAlex

) and comparable to polymeric surfaces. The force per width required to remove ice on the QC surface was even lower than that of a silicone (Sylgard 184) surface for an ice length of 7.0 cm. The low interfacial toughness of the erosion-resistant materials with ice was also retained after 1000 cycles of linear abrasion under a pressure of 27.0 kPa. The findings of this work expand the material selection options for durable large-scale ice-phobic applications and could enlighten the use of erosion-resistant materials in harsh industrial environments requiring effective de-icing.

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 score0.014
Threshold uncertainty score0.907

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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