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Record W4399993470 · doi:10.1016/s2352-3026(24)00143-1

Local radiotherapy and measurable residual disease-driven immunotherapy in patients with early-stage follicular lymphoma (FIL MIRO): final results of a prospective, multicentre, phase 2 trial

2024· article· en· W4399993470 on OpenAlexfundno aff
Alessandro Pulsoni, Simone Ferrero, Maria Elena Tosti, Stefano Luminari, Alessandra Dondi, Federica Cavallo, Francesco Merli, Anna Marina Liberati, Natalia Cenfra, Daniela Renzi, Manuela Zanni, Carola Boccomini, Andrés J.M. Ferreri, Sara Rattotti, Vittorio Ruggero Zilioli, Silvia Bolis, Patrizia Bernuzzi, Gerardo Musuraca, Gianluca Gaidano, Tommasina Perrone, Caterina Stelitano, Alessandra Tucci, Paolo Corradini, Sara Bigliardi, Francesca Re, Emanuele Cencini, Clara Mannarella, Donato Mannina, Melania Celli, Monica Tani, Giorgia Annechini, Giovanni Manfredi Assanto, Lavinia Grapulin, Anna Guarini, Marzia Cavalli, Lucia Anna De Novi, Riccardo Bomben, Elena Ciabatti, Elisa Genuardi, Daniela Drandi, Irene Della Starza, Luca Arcaini, Umberto Ricardi, Valter Gattei, Sara Galimberti, Marco Ladetto, Robin Foà, Ilaria Del Giudice

Bibliographic record

VenueThe Lancet Haematology · 2024
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
FundersAssociazione Italiana per la Ricerca sul CancroNovartisSierra OncologyGlaxoSmithKline
KeywordsMedicineFollicular lymphomaRadiation therapyRituximabOncologyStage (stratigraphy)LymphomaInternal medicineImmunotherapyCD20Follicular phaseCancer

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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 designNon-randomized 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

Citations5
Published2024
Admission routes1
Has abstractno

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