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Rectus sheath hematoma

2023· article· en· W4390022320 on OpenAlexaffabout
Mohamed Toufic El Hussein, Dona Job

Bibliographic record

VenueThe Nurse Practitioner · 2023
Typearticle
Languageen
FieldMedicine
TopicCase Reports on Hematomas
Canadian institutionsRockyview General HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineUnit (ring theory)MountHealth boardNursingGeneral hospitalFamily medicineGeneral surgeryEmergency medicinePsychologyEngineering

Abstract

fetched live from OpenAlex

Mohamed Toufic El Hussein is a professor in the School of Nursing and Midwifery, Faculty of Health, Community & Education at Mount Royal University in Calgary, Alberta, Canada; a clinical associate in the Faculty of Nursing at the University of Alberta in Edmonton, Alberta, Canada; and an acute care NP in Medical Cardiology in the Coronary Care Unit at Rockyview General Hospital in Calgary, Alberta, Canada. Dona Job is an RN in the ED at Rockyview General Hospital, Alberta Health Services in Calgary, Alberta, Canada. The authors have disclosed no potential conflicts of interest, financial or otherwise.

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)0.005
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.029
GPT teacher head0.335
Teacher spread0.306 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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