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Record W655758603

Скрининг рака молочной железы у женщин

2009· article· ru· W655758603 on OpenAlexaboutno aff
В. Ш. Навесова

Bibliographic record

VenueМедицинский вестник Башкортостана · 2009
Typearticle
Languageru
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerMammographyMedicineDiseaseCancerDeveloping countryDeveloped countryGynecologyFamily medicineEnvironmental healthPathologyPopulationInternal medicineEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

Clause is presented in the form of the review of literary data on mammography to screening of a breast cancer. The breast cancer continues to remain a serious medical and social problem in many developed countries, and last years and his frequency grows in developing countries. In industrially developed countries relative density breast cancer makes about 27 %. In 2000y. breast cancer has been revealed at 471 thousand women in developing countries. Among methods of diagnostics of a breast cancer, used for screening this disease, clinical inspection and self-inspection of mammary glands are considered as the most significant mammography. Mammography diagnostics one of leading methods of revealing of a breast cancer. Its basic advantage is the opportunity of diagnostics concerning early forms of disease, including the minimal and not palpated tumors. The analysis of references has shown growth of disease by a breast cancer in the CIS countries, the Europe, the USA and Canada. It testifies that the problem of early diagnostics of disease is rather actual.

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)0.001
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: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0270.010

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 head0.046
GPT teacher head0.312
Teacher spread0.267 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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