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Record W4303520550 · doi:10.30683/1929-2279.2022.11.03

Ascorbic Acid in Combination with Chemotherapeutic Agents for Cancer

2022· article· en· W4303520550 on OpenAlexvenueno aff
Michael J. González, Jorge R. Miranda-Massari, Jorgé Duconge, Miguel J. Berdiel, José Olalde

Bibliographic record

VenueJournal of cancer research updates · 2022
Typearticle
Languageen
FieldNursing
TopicVitamin C and Antioxidants Research
Canadian institutionsnot available
Fundersnot available
KeywordsAscorbic acidVitamin CMedicineVitaminCancerIn vivoAdjuvantCancer chemotherapyLife expectancyChemotherapyPharmacologySurgeryInternal medicineChemistryBiotechnologyBiologyPopulationFood scienceEnvironmental health

Abstract

fetched live from OpenAlex

Cancer accounts for nearly one-quarter of deaths in the United States. The life expectancy after standard treatment for these patients is dismal. New treatment modalities should be considered and evaluated. Ascorbic Acid (AA, Vitamin C) is a relatively low cost and safe nutrient even when given at very high doses (intravenous) that could be a very relevant co-adjuvant in cancer treatment. In vitro and in vivo studies have shown benefit of using high dose intravenous vitamin C as adjuvant therapy in cancer patients. There is significant supporting evidence of the benefits of the use vitamin C with chemotherapy.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.083
GPT teacher head0.446
Teacher spread0.362 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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