IGFBP-7 expression in human breast cancer and association with proliferation and cell cycle aberrations
Bibliographic record
Abstract
While advances in science and technology have increased options for treating breast cancer, current social trends have changed the way people deal with this disease.Women in the United States are no longer simply passive patients, but rather they are survivors, advocates and activists who are speaking up for themselves and speaking out for issues relevant to the treatment and prevention of breast cancer.As the discoveries of basic science have been translated to better clinical treatment, a new sense of hope has emerged.Quality of life now shares the spotlight with quantity of life as breast cancer has shifted from an acute to a chronic condition and as the numbers of long-term survivors increase.While this new population tends to have more optimistic expectations for survival, they are also expressing concerns about issues affecting their lives through and beyond treatment.These issues include, but are not limited to, such concerns as efficient and accurate diagnosis, the complexity of treatment decisions, access to quality cancer care, informed consent, privacy issues, availability of supportive care treatments, and effective communication skills, especially with their physicians.Survivors are also concerned about the impact of their disease on spouses and family, on fertility and sexuality issues, on their employment and (in the USA) insurability, and on their long-term survival.The identification of these increasing issues has given rise to a consumer movement that encourages a shift away from powerless victim to empowered survivor.Historically, breast cancer advocates asked for increased educational and supportive care resources.As the survivorship movement matured, new responsibilities and differing agendas arose amongst these groups.Some organizations defined their mission as one that would raise funds to support scientific research.Others felt compelled to raise awareness about early detection and treatment, controversial environmental issues, and prevention or risk reduction.A few organizations later entered the more political arenas and began lobbying for issues related to health care delivery, clinical trials access, and quality cancer care.Meanwhile, these many and varied missions are all helping to define an international agenda for breast cancer research and care, to guarantee the inclusion of consumer voices in most levels of decision-making, and to create partnerships between patients with breast cancer and the professionals who care for them.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".