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Record W4309412449 · doi:10.1016/s1470-2045(22)00656-8

5-year outcomes after stereotactic ablative body radiotherapy for primary renal cell carcinoma: an individual patient data meta-analysis from IROCK (the International Radiosurgery Consortium of the Kidney)

2022· review· en· W4309412449 on OpenAlexaff
Shankar Siva, Muhammad Ali, Rohann Correa, Alexander Muacevic, Lee Ponsky, Rodney J. Ellis, Simon S. Lo, Hiroshi Onishi, Anand Swaminath, Mark F. McLaughlin, Scott C. Morgan, Fabio Cury, Bin S. Teh, Anand Mahadevan, Irving Kaplan, William Chu, William Grubb, Raquibul Hannan, Michael Staehler, Andrew Warner, Alexander V. Louie

Bibliographic record

VenueThe Lancet Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsHealth Sciences CentreUniversity of TorontoUniversity of OttawaOttawa HospitalCancer Care OntarioMcMaster UniversitySunnybrook Health Science CentreMcGill University Health CentreJuravinski Cancer Centre
FundersCancer Council Tasmania
KeywordsSABR volatility modelMedicineRenal cell carcinomaRadiosurgeryCyberknifeRadiation therapyClinical endpointDiscontinuationUrologyInternal medicineSurgeryClinical trial

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.658
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.209
GPT teacher head0.379
Teacher spread0.170 · 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 designMeta-analysis
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

Citations133
Published2022
Admission routes1
Has abstractno

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