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An In Vivo Comparative Analysis of the Intra-Operative Properties of Injectable Calcium Phosphate/Calcium Sulphate Based Bone Cements

2007· article· en· W2026365837 on OpenAlexaboutno aff
Peter J. Catalano, Gerard Insley, Brian Hess

Bibliographic record

VenueKey engineering materials · 2007
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsnot available
Fundersnot available
KeywordsCalciumCranioplastyMaterials scienceIn vivoBiomedical engineeringCalcium phosphate cementBone cementDentistryCementMedicineComposite materialMetallurgySurgery

Abstract

fetched live from OpenAlex

The aim of this work was to assess the mixing, transfer and handling, properties, injectability, set time, wash-out characteristics, acceptance of hardware (i.e. stainless screws), and their delivery/transfer systems of self hardening synthetic bone cements made from calcium phosphate and calcium sulphate. Surgical procedures (i.e. cranioplasty) were performed on adult Labrador dogs using seven different bone cements from various manufacturers. Direct comparison of the defined intraoperative properties were evaluated and recorded. There is considerable variability with respect to application properties among commercially available injectable synthetic bone cements. Only one product was rated good to excellent in seven of the eight categories evaluated (6-excellent, 1-good, 1-fair) based on in-vivo tests. This study outlines the critical parameters required for successful implantation of cements that have to be understood when designing new injectable bone cements for the future.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.028
GPT teacher head0.292
Teacher spread0.264 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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