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Record W4400008657 · doi:10.21203/rs.3.rs-4410500/v1

Multi-omic analysis of SDHB-deficient pheochromocytomas and paragangliomas identifies metastasis and treatment-related molecular profiles

2024· preprint· en· W4400008657 on OpenAlexaff
Richard W. Tothill, Aidan Flynn, Andrew Pattison, Shiva Balachander, Emma Boehm, Blake Bowen, Trisha Dwight, Fernando J. Rossello, Oliver Hofmann, Luciano G. Martelotto, Magnus Zethoven, Lawrence S. Kirschner, Tobias Else, Lauren Fishbein, Anthony J. Gill, Arthur S. Tischler, Thomas J. Giordano, Jane R. Noble, Tamara Prodanov, Roger R. Reddel, Alison H. Trainer, Hans K. Ghayee, Isabelle Bourdeau, Marianne S. Elston, Nur Diana Binte Ishak, Rodney J. Hicks, Joakim Crona, Tobias Åkerström, Peter Stålberg, Patricia L. M. Dahia, Sean M. Grimmond, Roderick Clifton‐Bligh, Karel Pacák

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institutes of Health
KeywordsSDHBParagangliomaPheochromocytomaBiologyMetastasisCancer researchMutantMutationGermline mutationPathologyMedicineCancerGeneticsGeneEndocrinology

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.405
Teacher spread0.341 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations4
Published2024
Admission routes1
Has abstractno

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