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Record W1993397944 · doi:10.1097/opx.0b013e3181da863e

The Impact of Contact Angle on the Biocompatibility of Biomaterials

2010· article· en· W1993397944 on OpenAlexaff
Kara L. Menzies, Lyndon Jones

Bibliographic record

VenueOptometry and Vision Science · 2010
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBiocompatibilityContact lensBiocompatible materialBiomaterialContact angleWettingMaterials scienceBiomedical engineeringNanotechnologyMedicineOphthalmologyComposite material

Abstract

fetched live from OpenAlex

Biomaterials may be defined as artificial materials that can mimic, store, or come into close contact with living biological cells or fluids and are becoming increasingly popular in the medical, biomedical, optometric, dental, and pharmaceutical industries. Within the ophthalmic industry, the best example of a biomaterial is a contact lens, which is worn by approximately 125 million people worldwide. For biomaterials to be biocompatible, they cannot illicit any type of unfavorable response when exposed to the tissue they contact. A characteristic that significantly influences this response is that related to surface wettability, which is often determined by measuring the contact angle of the material. This article reviews the impact of contact angle on the biocompatibility of tissue engineering substrates, blood-contacting devices, dental implants, intraocular lenses, and contact lens materials.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.429
Teacher spread0.412 · 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

Citations549
Published2010
Admission routes1
Has abstractyes

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