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Record W4394762048 · doi:10.1055/s-0044-1782669

Corrigendum: Grade 3 Meningioma Survival and Recurrence Outcomes in an International Multicenter Cohort

2024· erratum· en· W4394762048 on OpenAlexaff
Kira Tosefsky, Alexander D. Rebchuk, Justin Z. Wang, Yosef Ellenbogen, Richard Drexler, Franz Ricklefs, Thomas Sauvigny, Ulrich Schüller, Christopher Cutler, Brandon Lucke‐Wold, Yusuf Mehkri, Sanju Lama, Garnette R. Sutherland, Michael Karsy, Brian L. Hoh, Manfred Westphal, Gelareh Zadeh, Stephen Yip, Serge Makarenko

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2024
Typeerratum
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity of CalgaryUniversity of TorontoHotchkiss Brain InstituteUniversity of British Columbia
Fundersnot available
KeywordsMedicineCohortMeningiomaInternal medicineOncologyRadiology

Abstract

fetched live from OpenAlex

Correction to: Grade 3 Meningioma Survival and Recurrence Outcomes in an International Multicenter Cohort J Neurol Surg B Skull Base 2024; 85(S 01): S073 DOI: 10.1055/s-0044-1779888 It has been brought to the publisher's attention that there are 19 authors for this abstract (no. S073) published in Journal of Neurological Surgery Part B: Skull Base , volume 85, number 01, S47 (DOI: 10.1055/s-0044-1779888 ), instead of one. All author names and affiliations are as mentioned above. Publication History Article published online: 14 March 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Stuttgart · New York

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)0.002
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0310.010

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 head0.086
GPT teacher head0.320
Teacher spread0.235 · 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 designObservational
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

Citations0
Published2024
Admission routes1
Has abstractyes

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