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Quality assurance practices for point of care testing programs: Recommendations by the Canadian society of clinical chemists point of care testing interest group

2020· review· en· W3108574884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueClinical Biochemistry · 2020
Typereview
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsCanadian Electricity AssociationOttawa Hospital
Fundersnot available
KeywordsPoint-of-care testingQuality assuranceMedicineQuality (philosophy)Medical physicsPatient careQuality managementTest (biology)Operations managementExternal quality assessmentNursingEngineeringPathologyManagement system

Abstract

fetched live from OpenAlex

Point of Care Testing (POCT) refers to clinical laboratory testing performed outside the central laboratory, nearer to the patient and sometimes at the patient bedside. The testing is usually performed by clinical staff, such as physicians or nurses, who are not laboratory trained. This document was developed by the POCT Interest group of the Canadian Society of Clinical Chemists (CSCC) as practical guidance for quality assurance practices related to POCT performed in hospital and outside hospital environments. The aspects of quality assurance addressed in this document include: (1) device selection, (2) initial device verification, (3) ongoing device verification, (4) ongoing quality assurance including reagent and quality control (QC) lot changes, and (5) quality management including operator and document management.

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.

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)0.008
metaresearch head score (Gemma)0.202
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.202
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.443
GPT teacher head0.556
Teacher spread0.113 · 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