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Record W4391312188 · doi:10.3390/jfb15020033

The Use of Functional Biomaterials in Aesthetic and Functional Restoration in Orbital Surgery

2024· article· en· W4391312188 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

VenueJournal of Functional Biomaterials · 2024
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsMcGill UniversityQueen's UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsModalitiesMaterials scienceMedicineSurgery

Abstract

fetched live from OpenAlex

The integration of functional biomaterials in oculoplastic and orbital surgery is a pivotal area where material science and clinical practice converge. This review, encompassing primary research from 2015 to 2023, delves into the use of biomaterials in two key areas: the reconstruction of orbital floor fractures and the development of implants and prostheses for anophthalmic sockets post-eye removal. The discussion begins with an analysis of orbital floor injuries, including their pathophysiology and treatment modalities. It is noted that titanium mesh remains the gold standard for orbital floor repair due to its effectiveness. The review then examines the array of materials used for orbital implants and prostheses, highlighting the dependence on surgeon preference and experience, as there are currently no definitive guidelines. While recent innovations in biomaterials show promise, the review underscores the need for more clinical data before these new materials can be widely adopted in clinical settings. The review advocates for an interdisciplinary approach in orbital surgery, emphasizing patient-centered care and the potential of biomaterials to significantly enhance patient outcomes.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.093
GPT teacher head0.275
Teacher spread0.181 · 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