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Record W4311860782 · doi:10.1111/ctr.14877

The John S. Najarian symposium: The past, present, and future of surgery and transplantation, May 20, 2022, Minneapolis, MN

2022· article· en· W4311860782 on OpenAlexaff
Mary E. Knatterud, Richard L. Simmons, William D. Payne, Peter G. Stock, Blanche M. Chavers, Nancy L. Ascher, Dixon B. Kaufman, Allan D. Kirk, Shaf Keshavjee, Abhinav Humar, Swaytha Ganesh, Christopher B. Hughes, Raja Kandaswamy, Arthur J. Matas

Bibliographic record

VenueClinical Transplantation · 2022
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHonorTransplantationMedicineGeneral surgeryCoronavirus disease 2019 (COVID-19)GerontologySurgeryInternal medicineDisease

Abstract

fetched live from OpenAlex

Dr John S Najarian (1927-2020), chairman of the Department of Surgery at the University of Minnesota from 1967 to 1993, was a pioneer in surgery, clinical immunology and transplantation. A Covid-delayed Festschrift was held in his honor on May 20, 2022. The speakers reflected on his myriad contributions to surgery, transplantation, and resident/fellow training, as well as current areas of ongoing research to improve clinical outcomes. Of note, Dr Najarian was a founder of the journal Clinical Transplantation.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0300.010

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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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