OT2-03-01: Incidence of Mastalgia as a Presenting Complaint in Iranian Population with Regard to Age, BMI, Education, Residency (City or Rural), State of Marriage and Compare with Western Countries.
Bibliographic record
Abstract
Abstract As it is has usually been stated, breast pain (mastalgia) is among the most common (or the commonest) cause of women referring to a breast clinic. The incidence has been reported in different ranges, and some studies (e.g. Canadian groups) have stated that mastalgia has its lowest incidence in middle east (compared to western countries). Based on this information, I have recently planned a study to investigate this issue. To evaluate this data, I planned a questionnaire for every new patient coming to my breast clinic randomly. Every questionnaire was double checked & if still incomplete, was completed by phone communication. The only inclusion criteria were to be a new patient. In this way over 550 questioners were completed during over 4 months. The aim is to find if there is any statistical difference in incidence rate and if there is any, evaluate any demographic difference that can be a cause. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr OT2-03-01.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".