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Record W4285519764 · doi:10.21037/acs-2021-bav-207

The need for comprehensive multidisciplinary programs, complex interventions, and precision medicine for bicuspid aortic valve disease

2022· review· en· W4285519764 on OpenAlexaff
Erin Crawford, Patrick M. McCarthy, S. Chris Malaisrie, Christopher K. Mehta, Jyothy Puthumana, Joshua D. Robinson, Michael Markl, Robert O. Bonow, Paul W.M. Fedak

Bibliographic record

VenueAnnals of Cardiothoracic Surgery · 2022
Typereview
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsBicuspid aortic valveMedicineMultidisciplinary approachPsychological interventionReferralDiseaseIntervention (counseling)Multidisciplinary teamIntensive care medicineAortic valveSurgeryInternal medicineFamily medicineNursing

Abstract

fetched live from OpenAlex

Patients with bicuspid aortic valves commonly require an intervention on their valve and/or aorta. Because of their heterogeneous presentations, recommendations for imaging surveillance and surgery timing are highly individualized. Critical points in care include time of diagnosis, transition from adolescent to adult medicine, and surgery referral. To better support patients with bicuspid aortic valves, we developed a comprehensive program that utilizes the multidisciplinary care team, complex interventions, and translational research protocols. We describe our program structure and experience with this common and sometimes challenging diagnosis.

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)0.002
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.526
GPT teacher head0.501
Teacher spread0.025 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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