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Record W4313222828 · doi:10.1007/s43678-022-00431-9

Does point-of-care ultrasonography improve diagnostic accuracy in emergency department patients with undifferentiated hypotension? An international randomized controlled trial from the SHOC-ED investigators

2022· article· en· W4313222828 on OpenAlexaff
M. Peach, J. Milne, Laura Diegelmann, Hein Lamprecht, Melanie Stander, D. Lussier, Chau Pham, Ryan Henneberry, Jacqueline Fraser, Kavish Chandra, Michael Howlett, Jay Mekwan, B. Ramrattan, Joanna Middleton, Daniël J. van Hoving, Luke Taylor, Tara Dahn, Sean Hurley, Kayla MacSween, L. Richardson, George Stoica, Samuel F. Hunter, Paul Olszynski, David Lewis, Paul Atkinson

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversity of OttawaRoyal University HospitalMemorial University of NewfoundlandUniversity of ManitobaSaint John Regional HospitalHealth Sciences CentreUniversity of SaskatchewanFraser HealthHorizon Health NetworkDalhousie University
Fundersnot available
KeywordsMedicineEmergency departmentRandomized controlled trialCardiogenic shockOdds ratioDiagnostic accuracyProtocol (science)Medical diagnosisShock (circulatory)Clinical endpointUltrasonographyEmergency medicineInternal medicineSurgeryRadiologyPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.004
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 head0.027
GPT teacher head0.315
Teacher spread0.288 · 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 designRandomized trial
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

Citations9
Published2022
Admission routes1
Has abstractno

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