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Record W2574380159 · doi:10.1182/blood.v126.23.329.329

Tosedostat Plus Low Dose Cytarabine Induces a High Rate of Responses That Can be Predicted By Genetic Profiling in Elderly AML

2015· article· en· W2574380159 on OpenAlexaff
Giuseppe Visani, Federica Loscocco, Fabio Fuligni, Eliana Zuffa, Alberto Sensi, Alfonso Zaccaria, Gerardo Musuraca, Barbara Giannini, Alessandro Lucchesi, Francesca Fabbri, Anna Maria Mianulli, Patrizia Tosi, Michela Tonelli, Anna Candoni, Renato Fanin, Giovanni Sparaventi, Marco Gobbi, Marino Clavio, Marco Rocchi, Pier Paolo Piccaluga, Alessandro Isidori

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsCytarabineMedicineInternal medicineMyeloid leukemiaChemotherapyProspective cohort studyGastroenterologyInduction chemotherapyOncologySurgery

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.268
Teacher spread0.238 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2015
Admission routes1
Has abstractyes

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