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Record W1513883988

Properties of a hybrid plaster-fibreglass cast.

2000· article· en· W1513883988 on OpenAlexaff
M N Charles, David Yen

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsQueen's University
Fundersnot available
KeywordsStiffnessMedicineComposite materialBendingMaterials science
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the suitability of a plaster-fibreglass hybrid cast for orthopedic applications, comparing them to plaster of Paris (POP) and fibreglass constructs. METHOD: Groups of 10 standardized hybrid, POP and fibreglass casts were studied. An Instron servohydraulic system was used to test the casts in 3-point bending and shear. OUTCOME MEASURES: Strength, stiffness, weight, thickness and cost of the 3 types of cast, and shear strength at the interface between the POP and fibreglass in the hybrid casts. RESULTS: The hybrid casts were twice as strong as the POP constructs, were stiffer and weighed 14% less but were thicker and cost 2.5 times more. They were almost as strong as and less than half the cost of the fibreglass constructs but were thicker, not as stiff, and weighed 42% more. The shear strength of the POP-fibreglass interface in the hybrid casts was higher than the 3-point bending strength of this construct by a factor of 3. CONCLUSIONS: Plaster-fibreglass hybrid casts should be considered for orthopedic use on the basis of their strength, stiffness, weight and cost, combined with their acknowledged advantages of good moulding ability and water resistance.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.202
Teacher spread0.176 · 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

Citations18
Published2000
Admission routes1
Has abstractyes

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