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Profiency testing in reticulocyte counting

2008· article· en· W2047232602 on OpenAlexaffabout
Reinhard Lohmann, Linda N. Crawford, D.E. Wood

Bibliographic record

VenueClinical & Laboratory Haematology · 2008
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsSystems, Applications & Products in Data Processing (Canada)Victoria Hospital
Fundersnot available
KeywordsReticulocyteReliability (semiconductor)Coefficient of variationStatisticsMedical physicsQuality (philosophy)MedicineReliability engineeringMathematicsBiologyEngineering

Abstract

fetched live from OpenAlex

The Laboratory Proficiency Testing Program tests and evaluates proficiency of clinical laboratories in Ontario, Canada. The programme began in 1974; testing of reticulocyte counts was added in 1982. From the beginning, the goal of the programme has been to ensure that the quality of practice in Ontario laboratories facilitates good quality patient care. Testing of indirect counting methods for reticulocytes is accomplished by the distribution of stained blood films. Performance is expressed in terms of accuracy and precision. Proficiency is assessed by comparing submitted results to an all-methods' mean and result reliability by observing the coefficient of variation (CV) of the cohort. The quality of the results vary neither with the manual counting system used nor the type of laboratory. The CV commonly ranges from 25 to 30%, and this lack of accuracy appears to be inherent in the technology of manual reticulocyte counting. We conclude that manual reticulocyte counting is technologically obsolete but may be of clinical value if used in a qualitative fashion. It should probably be replaced by an automated method.

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)0.003
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.204
GPT teacher head0.445
Teacher spread0.241 · 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

Citations12
Published2008
Admission routes2
Has abstractyes

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