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Record W1971879262 · doi:10.1016/j.ejvs.2011.12.006

Why the United States Center for Medicare and Medicaid Services (CMS) Should not Extend Reimbursement Indications for Carotid Artery Angioplasty/Stenting

2012· letter· en· W1971879262 on OpenAlexaff
Anne L. Abbott, Mark A. Adelman, Andrei V. Alexandrov, Henry J.M. Barnett, Jonathan Beard, Peter Bell, Martin Björck, David Blacker, Clifford J. Buckley, Richard P. Cambria, Anthony J. Comerota, E. Sander Connolly, Alun H. Davies, Hans‐Henning Eckstein, Rishad M. Faruqi, Gustav Fraedrich, Péter Gloviczki, Graeme J. Hankey, Robert E. Harbaugh, Eitan Heldenberg, Steven J. Kittner, Timothy Kleinig, Dimitri P. Mikhailidis, Wesley S. Moore, Ross Naylor, Andrew Nicolaides, Kosmas I. Paraskevas, David M. Pelz, James W. Prichard, Grant Purdie, Jean‐Baptiste Ricco, Thomas S. Riles, Peter M. Rothwell, Peter Sandercock, Henrik Sillesen, J. David Spence, Francesco Spinelli, Aron Tan, Ankur Thapar, Frank J. Veith, Wei Zhou

Bibliographic record

VenueEuropean Journal of Vascular and Endovascular Surgery · 2012
Typeletter
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineMedicaidReimbursementAngioplastyCarotid arteriesCenter (category theory)General surgeryCardiologyInternal medicineHealth care

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.040
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.123
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.1230.073
Insufficient payload (model declined to judge)0.0090.006

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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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
GenreCommentary

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

Citations26
Published2012
Admission routes1
Has abstractno

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