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Record W2166586591 · doi:10.1093/carcin/bgv034

The impact of low-dose carcinogens and environmental disruptors on tissue invasion and metastasis

2015· review· en· W2166586591 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCarcinogenesis · 2015
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsHealth Canada
FundersNational Cancer InstituteUniversità degli Studi di FirenzeNational Institute on Minority Health and Health DisparitiesNational Institute of Environmental Health SciencesFondazione Cariplo
KeywordsCarcinogenMetastasisCancerMedicineCancer researchBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

The purpose of this review is to stimulate new ideas regarding low-dose environmental mixtures and carcinogens and their potential to promote invasion and metastasis. Whereas a number of chapters in this review are devoted to the role of low-dose environmental mixtures and carcinogens in the promotion of invasion and metastasis in specific tumors such as breast and prostate, the overarching theme is the role of low-dose carcinogens in the progression of cancer stem cells. It is becoming clearer that cancer stem cells in a tumor are the ones that assume invasive properties and colonize distant organs. Therefore, low-dose contaminants that trigger epithelial-mesenchymal transition, for example, in these cells are of particular interest in this review. This we hope will lead to the collaboration between scientists who have dedicated their professional life to the study of carcinogens and those whose interests are exclusively in the arena of tissue invasion and metastasis.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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 head0.039
GPT teacher head0.351
Teacher spread0.312 · 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