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Record W1596644163 · doi:10.25011/cim.v35i3.16586

Bone marrow aspirate collection and preparation – A comparison of three methods

2012· article· en· W1596644163 on OpenAlexaffvenueabout
Teresa DiFrancesco, Duane J. Boychuk, John Lafferty, Mark Crowther

Bibliographic record

VenueClinical and investigative medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicHematological disorders and diagnostics
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University Medical CentreHamilton Regional Laboratory Medicine Program
Fundersnot available
KeywordsMedicineBone marrow aspirateReadabilityBone marrowCoagulation testingSurgeryPathologyInternal medicineCoagulationComputer science

Abstract

fetched live from OpenAlex

PURPOSE: Preparing bone marrow smears using non-anticoagulated bone marrow aspirate is a traditional practice but many laboratories now use anticoagulated aspirate samples in K-EDTA. There are no published studies comparing the effectiveness of these two methods. This report compares the readability of slides, prepared using non-anticoagulated and anticoagulated methods, from three laboratories in Hamilton Ontario. METHODS: A blinded set of 129 aspirate slides prepared using anticoagulated and non-anticoagulated methodologies (using K-EDTA) was reviewed by three reviewers. Slides were classified as unreadable if two of the three observers rejected them based on a standardized survey. RESULTS: The proportion of slides classed as unreadable varied widely (5.0% to 46.9%) depending on collection and slide preparation methods. Degree of coagulation did not affect readability. CONCLUSION: A measurable advantage to using non-anticoagulated bone marrow was not demonstrated. Immediate anticoagulation of bone marrow samples, with laboratory personnel at the bedside to assess sample quality, followed by slide preparation in the laboratory provided the best results.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
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 head0.367
GPT teacher head0.486
Teacher spread0.119 · 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 designObservational
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

Citations7
Published2012
Admission routes3
Has abstractyes

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