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Record W70673441

Evolution of Point-of-Care Testing in Australia.

2010· article· en· W70673441 on OpenAlexaff
Rosy Tirimacco

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsVictoria Park
Fundersnot available
KeywordsPoint-of-care testingAccreditationInterimMedicineQuality (philosophy)Government (linguistics)Health careMedical educationPathologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Currently no mandatory standards or guidelines exist for Point-of-Care Testing (PoCT) in Australia. In 2001, a report on the role and value of 'near patient testing' in general practice outlined work that was required to assist the Australian Government to decide how to manage PoCT. Phillips Fox reported that adoption of mandatory accreditation requirements was not justified by the level of risk associated with PoCT. If implemented appropriately, PoCT could be useful with frontline management of chronic disease, relieving stress on general practice and expanding the reach of pathology. Interim PoCT standards in general practice were developed by a Quality Use of Pathology committee, and formed an accreditation framework for the PoCT in General Practice Trial. This trial concluded that PoCT has a role in supporting the primary healthcare team to manage chronic disease patients. While results of the trial are still being considered, the potential impact of funding PoCT in general practice is being treated as part of the wider review of pathology funding currently taking place in Australia. Although Australia has local models from which to draw experience, it has yet to decide the quality framework it would adopt if it was to roll out PoCT in general practice. The quality framework that Australia adopts for PoCT must achieve high quality pathology results that enhance clinical care.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
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)0.0000.000

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 head0.095
GPT teacher head0.360
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2010
Admission routes1
Has abstractyes

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