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Record W2006163699 · doi:10.1191/1078155204jp127oa

Effects of flaxseed on breast cancer growth

2004· article· en· W2006163699 on OpenAlexafffund
Mário L de Lemos, Robin K O’Brien

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2004
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsBC Cancer Agency
FundersBC Cancer Agency
KeywordsMedicineBreast cancerTamoxifenCancerOncologyInternal medicineTraditional medicineGynecology

Abstract

fetched live from OpenAlex

The use of flaxseed (linseed) to combat breast cancer has attracted increased attention since the preliminary results of a clinical study were presented in the San Antonio Breast Cancer Symposium in December 2000. One of the most often quoted implications of the study was that the anti-tumour effect of flaxseed muffin may be comparable to that of tamoxifen. However, flax-seed also contains secoisolariciresinol diglycoside (SDG), which is converted by the gut bacteria into the oestrogenic lignans, enterodiol and enterolac-tone. Given that other plant-derived oestrogenic substances (phyto-oestrogens) can stimulate breast cancer growth under certain circusmtances, there are concerns regarding the safety of flaxseed. The following review will look at the existing data to help clarify some of these issues.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · 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
Metaresearch0.0000.000
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)0.0030.000

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 head0.027
GPT teacher head0.445
Teacher spread0.418 · 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 designObservational
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

Citations1
Published2004
Admission routes2
Has abstractyes

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