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Record W2945658519 · doi:10.24908/pocus.v2i3.13282

Case Report: A cardiac mass diagnosed using Point-of-care ultrasound in a dyspneic patient. An integrated ultrasound examination of lung-heart-Inferior Vena Cava

2017· article· en· W2945658519 on OpenAlexvenueno aff
Maria Viviana Carlino, Costantino Mancusi, Alfonso Sforza, Giorgio Bosso, Valentina Di Fronzo, Gaetana Ferro, Giovanni de Simone, Fiorella Paladino

Bibliographic record

VenuePOCUS Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInferior vena cavaCardiologyInternal medicineHeart failureVentricleFurosemideBlood pressureHeart rate

Abstract

fetched live from OpenAlex

A 74-year-old woman with history of hypertension presented to the Emergency Department (ED) with severe resting dyspnea and swelling in the feet, ankles and legs. She was on treatment with furosemide and a beta blocker. At the time of admission blood pressure was 145/88 mmHg, heart rate (HR) 99 bpm, regular, oxygen saturation was 89% (FiO2 21%) and respiratory rate was 17 breaths/min. Abbreviation List AST: Aspartate aminotransferase ED: Emergency Department GFR: Glomerular Filtration Rate HCC: Hepatocellular Carcinoma HF: Heart Failure HR: Heart rate IVC: Inferior vena cava LAFB: Left anterior fascicular block LV: Left ventricle NT-pro-BNP: N-Terminal pro-Brain Natriuretic peptide POCUS: Point-of-care ultrasound RA: Right atrium RBB: Right bundle branch block RV: Right ventricle TS: Tricuspid stenosis

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.356
Teacher spread0.318 · 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 designCase report
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

Citations1
Published2017
Admission routes1
Has abstractyes

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