MétaCan
Menu
Back to cohort
Record W3116150966 · doi:10.1016/j.cjco.2020.11.022

Ten Questions Cardiologists Should Be Able to Answer About Cardiac Sarcoidosis: Case-Based Approach and Contemporary Review

2020· review· en· W3116150966 on OpenAlexaff
Sylvain Lemay, Montse Massot, François Philippon, David Belzile, Pierre Yves Turgeon, Jonathan Beaudoin, Claudine Laliberté, Sophie Fortin, Geneviève Dion, Julie Milot, Mikaël Trottier, Justin Gosselin, Éric Charbonneau, David H. Birnie, Mario Sénéchal

Bibliographic record

VenueCJC Open · 2020
Typereview
Languageen
FieldMedicine
TopicSarcoidosis and Beryllium Toxicity Research
Canadian institutionsUniversity of OttawaUniversité LavalInstitut Universitaire de Cardiologie et de Pneumologie de Québec
FundersFundación Alfonso Martín Escudero
KeywordsSarcoidosisMedicineEtiologyCardiac sarcoidosisPresentation (obstetrics)DermatologyGynecologyPathologySurgery

Abstract

fetched live from OpenAlex

Sarcoidosis is an inflammatory multisystemic disease of unknown etiology characterized by the formation of noncaseating epithelioid cell granulomas. Cardiac sarcoidosis might be life-threatening and its diagnosis and treatment remain a challenge nowadays. The aim of this review is to provide an updated overview of cardiac sarcoidosis and, through 10 practical clinical questions and real-life challenging case scenarios, summarize the main clinical presentation, diagnostic criteria, imaging findings, and contemporary treatment.

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)0.004
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.264
GPT teacher head0.450
Teacher spread0.187 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCJC OpenSame topicSarcoidosis and Beryllium Toxicity ResearchFrench-language works237,207