Bibliographic record
Abstract
The 7th Annual Women’s Cancer Conference, cosponsored by the City of Hope (CA, USA) and the Nevada Cancer Institute, USA, convened in November 2007 at the Wynn Hotel in Las Vegas, Nevada. Lucille Leong and Robert Morgan, both from the City of Hope faculty, co-chaired the Women’s Cancer Conference and were pleased with the 260 attendees, 20% of whom had attended a prior Women’s Cancer Conference. The 3-day Women’s Cancer Conference is primarily directed towards the general oncologist and primary care physician seeking a more in-depth understanding of new cancer treatments and practice. The presenting faculty for the 2007 meeting came predominantly from the two host institutions, with additional speakers from around the USA. The Women’s Cancer Conference follows a case-based learning format: didactic lectures are followed by a series of individual case presentations, which are discussed in detail with full audience participation. It is estimated that over 680,000 women in the USA will develop cancer in 2007 and almost 290,000 will die of the disease. Although a decline in the use of menopausal hormone therapy has resulted in a decline in new breast cancers, breast cancer remains the most common malignancy to develop in women. Improvements in screening and therapy have been credited with the improved survival of women with early stage disease. In the USA, the leading causes of cancer-related deaths are lung, colorectal, pancreas and ovarian cancers. Worldwide, cervical cancer is a major cause of cancer mortality. The first day of the conference focused on the interdisciplinary approach to gynecologic malignancies. Lectures from oncologic surgeons, medical oncologists and pathologists highlighted the diagnosis and treatment of cervical and ovarian cancers. The human papilloma virus (HPV) is an oncogenic virus and a causative agent in cervical cancer. HPV is isolated in over 99% of all cancer specimens. The WHO has declared HPV to be the first identified ‘necessary cause’ of a human cancer. Although the routine use of PAP smears has decreased the incidence and death rate in ‘resource rich’ countries, worldwide cervical cancer continues to be a leading cause of cancer death in women. After reviewing the role of HPV in the pathogenesis of cervical cancer, Sharon Wilczynski summarized diagnostic testing for HPV. The Canadian Cervical Cancer Screening Trial compared conventional cervical cytologic testing (PAP) with FDA-approved HPV DNA testing in a population of 10,154 women aged 30–69 years who presented for routine screening. The HPV DNA test was more sensitive than the PAP – 94.5 compared with 55.4% and negative predictive values of 99.8 and 100%. A Swedish trial enrolled 12,527 women to PAP alone or to HPV DNA testing (PCR-immunoassay that is not FDA approved) plus PAP. Grade 2 or 3 cervical intraepithelial neoplasia (CIN) or cancer was identified in 51% more women undergoing both tests. However, the increased sensitivity of the HPV DNA test resulted in many more
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".