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Record W3000185397 · doi:10.1055/s-0039-3400035

Evaluation of onconutraceutical potential and chemical characterization of vegetable smoothies

2019· article· en· W3000185397 on OpenAlexaff
SF Rapa, Emanuela Salviati, D Cianciarulo, Giacomo Pepe, Daniela Coppola, Ludovico Coppola, Michele Manfra, Giuseppina Autore, Pietro Campiglia, Stefania Marzocco

Bibliographic record

VenuePlanta Medica · 2019
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsCardiotoxicityDoxorubicinNutraceuticalBreast cancerMedicineCardiac toxicityPharmacologyCancerToxicityInternal medicineChemotherapyPathology

Abstract

fetched live from OpenAlex

The research towards onconutraceutical products not only for cancer prevention but also as a valid support to the pharmacological therapies is of growing interest. Doxorubicin is one of the most potent and widely used chemotherapeutic agents for various tumors, as breast cancer. However, doxorubicin clinical application is limited by cumulative and dose-related cardiotoxicity, which may lead to congestive heart failure [1]. Thus, this study aims to identify possible nutraceutical matrices able to reduce the doxorubicin toxicity without modifying its antineoplastic activity on breast cancer cells.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 score0.023
Threshold uncertainty score0.242

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 head0.022
GPT teacher head0.264
Teacher spread0.241 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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