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Record W2998211851 · doi:10.1097/tp.0000000000003095

Recommended Treatment for Antibody-mediated Rejection After Kidney Transplantation: The 2019 Expert Consensus From the Transplantion Society Working Group

2019· review· en· W2998211851 on OpenAlexaff
Carrie A. Schinstock, Roslyn B. Mannon, Klemens Budde, Anita S. Chong, Mark Haas, Stuart J. Knechtle, Carmen Lefaucheur, Robert A. Montgomery, Peter Nickerson, Stefan G. Tullius, Curie Ahn, Medhat Askar, Marta Crespo, Steven J. Chadban, Sandy Feng, Stanley C. Jordan, Kwan Man, Michael Mengel, Randall E. Morris, Inish O’Doherty, B. Handan Özdemir, Daniel Serón, Anat R. Tambur, Kazunari Tanabe, Jean‐Luc Taupin, Philip J. O’Connell

Bibliographic record

VenueTransplantation · 2019
Typereview
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of AlbertaManitoba Health
FundersNational Institute of Allergy and Infectious DiseasesNational Institute on Aging
KeywordsMedicineIntensive care medicineTransplantationClinical trialRandomized controlled trialKidney transplantationConsensus conferencePathologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.044
metaresearch head score (Gemma)0.046
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: Review · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0050.003
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0070.004
Research integrity0.0100.013
Insufficient payload (model declined to judge)0.0050.004

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 head0.085
GPT teacher head0.370
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
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

Citations331
Published2019
Admission routes1
Has abstractyes

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