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Record W4388695427 · doi:10.55418/9781933477299

Disorders of the Heart and Blood Vessels

2023· book· en· W4388695427 on OpenAlexaff
Joseph J. Maleszewski, Allen Burke, John P. Veinot, William D. Edwards

Bibliographic record

VenueAmerican Registry of PathologyArlington, Virginia eBooks · 2023
Typebook
Languageen
FieldMedicine
TopicCardiac tumors and thrombi
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsNeoplastic diseaseCornerstoneMedicineBroad spectrumPresentation (obstetrics)Medical physicsMultidisciplinary approachDiseaseGreat vesselsPathologyRadiologySurgeryGeography

Abstract

fetched live from OpenAlex

This new volume on the heart and great vessels has been expanded to become a comprehensive atlas of all cardiovascular disease—both neoplastic and non-neoplastic. In the spirit of prior editions, correlation of expertly curated pathology photographs and photomicrographs with clinical presentation, imaging and molecular genetics remains the cornerstone. The spectrum of cardiovascular disease, both congenital and acquired, is vast; accounting for the relative size of this fascicle. Every attempt has been made to focus on the clinically-relevant features of the diseases helping not only pathologists, but also providing cardiologists, radiologists, and surgeons a reference to understand the pathologic basis of the conditions they diagnose and treat each day. The authors have meticulously provided gross photographs that mirror (where possible) planar imaging techniques that will enable pathologic-radiologic correlation and facilitate a multidisciplinary approach to 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 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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0630.037

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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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
GenreOther

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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueAmerican Registry of PathologyArlington, Virginia eBooksSame topicCardiac tumors and thrombiFrench-language works237,207