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Record W4231214847 · doi:10.1038/s41379-019-0244-6

Abstracts from USCAP 2019: Pulmonary Pathology (1803-1896)

2019· article· en· W4231214847 on OpenAlexafffund
Benjamin Adam, Katie Du, Silas Rotich, Michael Mengel, Khaled Alkhateeb, Youssef Khafateh, Mohammed Alghamdi, Tiffani Mathew, Mostafa Fraig, Wajd Althakfi, Andréanne Gagné, Patrice Desmeules, Michèle Orain, Philippe Joubert, Rania G. Aly, А. А. Теплов, Naohiro Uraoka, Kareem Ibrahim, Natasha Rekhtman, Meera Hameed, William D. Travis, Yukako Yagi, Ryota Ando, Tomomi Koide, Ai Ito, Ayami Kiriyama, Masahiko Fujino, Masafumi Ito

Bibliographic record

VenueModern Pathology · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsInstitut Universitaire de Cardiologie et de Pneumologie de QuébecUniversité LavalUniversity of Alberta
FundersBC Cancer AgencyBristol-Myers Squibb
KeywordsPathologyPulmonary pathologyMedicineAnatomical pathologyImmunohistochemistry

Abstract

fetched live from OpenAlex

Background: Transbronchial lung transplant biopsies (TBBx) are limited by non-specific histological lesions and suboptimal interobserver reproducibility. Gene expression offers a potentially more precise, objective and mechanistic diagnostic approach, but it has not yet been fully utilized in lung transplants. The aim of this study was to assess the utility of gene expression in formalin-fixed paraffin-embedded (FFPE) lung transplant biopsies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.006

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 head0.220
Teacher spread0.193 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2019
Admission routes2
Has abstractyes

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