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Record W4211044551 · doi:10.1177/08404704211057525

Digitally enabled supply chain as a strategic asset for the COVID-19 response in Alberta

2022· article· en· W4211044551 on OpenAlexafffundabout
Anne Snowdon, Alexandra Wright

Bibliographic record

VenueHealthcare Management Forum · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsUniversity of TorontoUniversity of Windsor
FundersCanadian Institutes of Health Research
KeywordsCoronavirus disease 2019 (COVID-19)Supply chain2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Asset (computer security)BusinessChain (unit)VirologyMarketingComputer scienceMedicineComputer securityOutbreakInternal medicine

Abstract

fetched live from OpenAlex

This provincial case study, one of seven conducted as part of a national research program on healthcare supply chain management during COVID-19, focuses on Alberta. With a history of emergency preparedness, Alberta's unique context, one that includes having an already established, centralized, and digital healthcare supply chain strategy, sets this case apart from the others in terms of pandemic responses. A key challenge navigated by Alberta was the inadequacies of traditional sourcing and procurement approaches to meet surges in product demand, which was overcome by the implementation of unique procurement strategies. Opportunities for Alberta included the integration of supply chain teams into senior leadership structures, which enabled access to data to inform public health decision-making. This case demonstrated how Alberta's healthcare supply chain assets-its supply chain infrastructure, data, and leadership expertise, especially-contributed to resilient supply chain capacity across the province.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.292
Teacher spread0.261 · 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 designNot applicable
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

Citations11
Published2022
Admission routes3
Has abstractyes

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