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Record W4233820885 · doi:10.1016/j.euf.2019.10.004

Reply to Francesco Montorsi, Alessandro Larcher, and Umberto Capitanio’s Letter to the Editor re: Rohann J.M. Correa, Alexander V. Louie, Nicholas G. Zaorsky, et al. The Emerging Role of Stereotactic Ablative Radiotherapy for Primary Renal Cell Carcinoma: A Systematic Review and Meta-Analysis. Eur Urol Focus. 2019 Jun 24. pii: S2405-4569(19)30157-9. https://doi.org/10.1016/j.euf.2019.06.002. [Epub ahead of print]

2019· review· en· W4233820885 on OpenAlexaff
Rohann Correa, Alexander V. Louie, Nicholas G. Zaorsky, Eric J. Lehrer, Rodney J. Ellis, Lee Ponsky, Irving Kaplan, Anand Mahadevan, William Chu, Anand Swaminath, Raquibul Hannan, Hiroshi Onishi, Bin S. Teh, Alexander Muacevic, Simon S. Lo, Michael Staehler, Shankar Siva

Bibliographic record

VenueEuropean Urology Focus · 2019
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsHealth Sciences CentreUniversity of TorontoJuravinski Cancer CentreSunnybrook Health Science CentreCancer Care Ontario
FundersVarian Medical SystemsAstraZeneca
KeywordsSABR volatility modelMedicineStereotactic radiotherapyAblative caseRenal cell carcinomaRadiation therapyRadiosurgerySurgeryInternal medicine

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 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)0.007
metaresearch head score (Gemma)0.057
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.015
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0030.002
Research integrity0.0150.017
Insufficient payload (model declined to judge)0.0080.006

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 head0.040
GPT teacher head0.296
Teacher spread0.256 · 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
GenreCommentary

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
Published2019
Admission routes1
Has abstractno

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