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Record W2977606974 · doi:10.1056/nejmc1813100

PCI Guided by Fractional Flow Reserve at 5 Years

2019· letter· en· W2977606974 on OpenAlexaff

Bibliographic record

VenueNew England Journal of Medicine · 2019
Typeletter
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFractional flow reserveConventional PCICardiologyInternal medicineMathematicsMedicine

Abstract

fetched live from OpenAlex

102and national groups in the initial identification of the condition as well as challenges in management and logistics.Mycyk further underscores the critical multiagency, multidisciplinary effort by groups such as the Illinois Poison Center, the Toxikon Consortium, the CDC, and the Illinois Department of Public Health.It was through the efforts of these organizations and the multidisciplinary collaborations of area hospital and emergency workers that the outbreak was recognized and effective treatment to achieve hemostasis and correct coagulopathy was initiated.Wang et al. address pharmacoeconomic considerations in the use of vitamin K 1 .They describe the higher cost of the oral formulation than the intravenous formulation and raise concerns about procurement during shortages.As we reported, this became a major issue in central Illinois and led some patients to obtain vitamin K 1 products from nonpharmaceutical online vendors.We recommended against this because of concerns about the purity of these supplements.Although local pharmacies were eventually able to acquire additional supplies from other states, a disseminated outbreak would require a coordi-nated effort to increase the availability of vitamin K 1 .We strongly support exploration of alternative sources of vitamin K 1 by the FDA in order to lower costs and circumvent future shortages.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0230.012
Insufficient payload (model declined to judge)0.0070.003

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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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 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

Citations3
Published2019
Admission routes1
Has abstractno

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