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Record W4309029787 · doi:10.1016/j.ijrobp.2022.09.009

LUSTRE: A Phase III Randomized Trial of Stereotactic Body Radiotherapy (SBRT) vs. Conventionally Hypofractionated Radiotherapy (CRT) for Medically Inoperable Stage I Non-Small Cell Lung Cancer (NSCLC)

2022· article· en· W4309029787 on OpenAlexaff
Anand Swaminath, Sameer Parpia, Marcin Wierzbicki, V. Kundapur, Sergio Faria, Gordon Okawara, Theodoros Tsakiridis, Naseer Ahmed, Alexis Bujold, Khalid Hirmiz, T.E. Owen, N. Leong, Kevin Ramchandar, Édith Filion, Harold Lau, A.V. Louie, Kimmen Quan, M. Levine, James R. Wright, Timothy J. Whelan

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsThunder Bay Regional Health Sciences CentreUniversity of CalgaryCentre Hospitalier de l’Université de MontréalHealth Sciences CentreCancerCare ManitobaWindsor Regional HospitalUniversité de MontréalHôpital Maisonneuve-RosemontSunnybrook Health Science CentreJuravinski Cancer CentreMcGill University Health CentreMcMaster University
Fundersnot available
KeywordsMedicineRandomized controlled trialRadiosurgeryLung cancerHazard ratioRadiation therapyClinical endpointStage (stratigraphy)Dose fractionationPneumonitisRadiologyNuclear medicineOncologyInternal medicineLungConfidence interval

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.002

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 head0.016
GPT teacher head0.360
Teacher spread0.344 · 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 designRandomized trial
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

Citations8
Published2022
Admission routes1
Has abstractno

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