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Record W1990759869 · doi:10.1016/s0840-4704(10)60542-x

Advancing the Health Care Supply Chain and Promoting Leadership through Strategic Partnerships with Industry

2008· article· en· W1990759869 on OpenAlexaboutno aff
Sanober S. Motiwala, Joan E. McLaughlin, John G. King, Brent Hodgson, Michael Hamilton

Bibliographic record

VenueHealthcare Management Forum · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipSupply chainBusinessSupply chain managementHealth careStrategic partnershipInformation sharingProcess (computing)Service (business)Process managementOperations managementKnowledge managementPublic relationsMarketingBusiness administrationPolitical scienceFinanceEconomicsComputer science

Abstract

fetched live from OpenAlex

While supply chain partnerships are common in the private industry, they are unique in health care. This article looks at the novel partnership between St. Michael's Hospital and Baxter Canada. By sharing information and working together, these organizations evaluated and tackled service disruptions caused by backorders. Their formal collaboration has resulted in a streamlined backorder management process, and more importantly, better and timelier patient 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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.118
GPT teacher head0.292
Teacher spread0.173 · 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 designTheoretical or conceptual
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

Citations9
Published2008
Admission routes1
Has abstractyes

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