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Influence of extracorporeal shock-wave application on normal bone in an animal model <i>in vivo</i>

2002· article· en· W4210381637 on OpenAlexaff
Markus Maier, Stefan Milz, Thomas Tischer, Wolfgang Münzing, N. Manthey, A. Stäbler, N. Holzknecht, Christoph Weiler, Michael Nerlich, H J Refior, Christoph Schmitz

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2002
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsCanadian Association of Physicists
Fundersnot available
KeywordsFemurBone marrowExtracorporealSoft tissueIn vivoMedicineNuclear medicineBlood flowAnatomyPathologyInternal medicineSurgeryBiology

Abstract

fetched live from OpenAlex

There is little information about the effects of extracorporeal shock-wave about application the effects (ESWA) of on normal bone physiology. We have therefore investigated the effects of ESWA on intact distal rabbit femora in vivo. The animals received 1500 shock-wave pulses each of different energy flux densities (EFD) on either the left or right femur or remained untreated. The effects were studied by bone scintigraphy, MRI and histopathological examination. Ten days after ESWA (0.5 mJ/mm 2 and 0.9 mJ/mm 2 EFD), local blood flow and bone metabolism were decreased, but were increased 28 days after ESWA (0.9 mJ/mm 2 ). One day after ESWA with 0.9 mJ/mm 2 EFD but not with 0.5 mJ/mm 2 , there were signs of soft-tissue oedema, epiperiosteal fluid and bone-marrow oedema on MRI. In addition, deposits of haemosiderin were found epiperiosteally and within the marrow cavity ten days after ESWA. We conclude that ESWA with both 0.5 mJ/mm 2 and 0.9 mJ/mm 2 EFD affected the normal bone physiology in the distal rabbit femur. Considerable damaging side-effects were observed with 0.9 mJ/mm 2 EFD on periosteal soft tissue and tissue within the bone-marrow cavity.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.226
Teacher spread0.204 · 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

Citations15
Published2002
Admission routes1
Has abstractyes

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