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Record W2101474899 · doi:10.1370/afm.668

Management of Venous Thromboembolism: A Clinical Practice Guideline from the American College of Physicians and the American Academy of Family Physicians

2007· article· en· W2101474899 on OpenAlexaff
Vincenza Snow, Amir Qaseem, Patricia P. Barry, E. Rodney Hornbake, Jonathan E Rodnick, Timothy Tobolic, Belinda Ireland, Jodi B Segal, Eric B Bass, Kevin B. Weiss, Lee A. Green, Douglas K Owens

Bibliographic record

VenueThe Annals of Family Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicinePulmonary embolismVenous thrombosisGuidelineVenous thromboembolismIncidence (geometry)ThrombosisIntensive care medicinePopulationDeep veinSurgeryPathology

Abstract

fetched live from OpenAlex

Venous thromboembolism is a common condition affecting 7.1 persons per 10,000 person-years among community residents. Incidence rates for venous thromboembolism are higher in men, African-Americans, and increase substantially with age. It is critical to treat deep venous thrombosis at an early stage to avoid development of further complications, such as pulmonary embolism or recurrent deep venous thrombosis. The target audience for this guideline is all clinicians caring for patients who have been given a diagnosis of deep venous thrombosis or pulmonary embolism. The target patient population is patients receiving a diagnosis of pulmonary embolism or lower-extremity deep venous thrombosis.

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)0.002
metaresearch head score (Gemma)0.008
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: Review · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.005

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 head0.140
GPT teacher head0.457
Teacher spread0.317 · 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
GenreReview

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

Citations61
Published2007
Admission routes1
Has abstractyes

Explore more

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