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Record W2765309154 · doi:10.1002/adhm.201770105

Osseointegrated Implants: Strategies for Optimizing the Soft Tissue Seal around Osseointegrated Implants (Adv. Healthcare Mater. 20/2017)

2017· article· en· W2765309154 on OpenAlexaff
Mohamed‐Nur Abdallah, Zahi Badran, Ovidiu Ciobanu, Nader Hamdan, Faleh Tamimi

Bibliographic record

VenueAdvanced Healthcare Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsDalhousie UniversityMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsOsseointegrationSoft tissueSeal (emblem)DentistryMedicineImplantSurgeryArt

Abstract

fetched live from OpenAlex

Establishing a strong soft tissue seal around bone-anchored implants, such as orthopedic and dental implants, is critical for preventing bacterial infections and enhancing their long-term success. The recent findings and challenges concerning the establishment of such a strong soft tissue attachment are reviewed by Mohamed-Nur Abdallah, Zahi Badran, Ovidiu Ciobanu, Nader Hamdan, and Faleh Tamimi in article number 1700549.

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 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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
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 score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.030
GPT teacher head0.318
Teacher spread0.288 · 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 teacher head, not a consensus.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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