MétaCan
Menu
Back to cohort

SARS

2004· article· en· W2315833758 on OpenAlexaff
Ron Zapp, Mel Krajden, Tim Lynch

Bibliographic record

VenueQuality Management in Health Care · 2004
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsBC Centre for Disease Control
Fundersnot available
KeywordsScrutinyDocumentationFront linePublic relationsMedicinePolitical scienceOperations managementOperations researchComputer scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Emergence of severe acute respiratory syndrome in March 2003 tested all aspects of BC Centre for Disease Control (BCCDC) operations. In addition to its public health responsibilities, BCCDC was pivotal in the science defining SARS. These events occurred under international scientific and media scrutiny over a 4-month period and were seen as an opportunity to learn about how the Centre performed under extreme pressure as a QM-based (quality-management-based) organization. A retrospective review of the QM practices over the previous 6-months was initiated on June 30, 2003. Key management documentation during the study period was reviewed. Structured interviews were conducted with front line personnel. Customized instrumentation was developed to correlate management decisions with recognized QM criteria: anticipatory management; keeping programs on track; ongoing adjustment, improvement, and revision; identifying and improving sources of error, waste, and redundancy; feedback from key stakeholders; and data-driven decision-making methods. The team structure between laboratory science and epidemiology was critical. This was attributed to the culture of scientific discovery of the organization. All knowledge gained was shared with other organizations around the world. The consensus is that British Columbia was very lucky this time around. This review is part of BCCDC's commitment to fighting emerging infectious diseases.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.065
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0650.027

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 head0.104
GPT teacher head0.437
Teacher spread0.333 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueQuality Management in Health CareSame topicSARS-CoV-2 detection and testingFrench-language works237,207