بررسی میزان تطابق نتایج حاصله از ارزیابی تست پاپ اسمیر با نتایج پاتولوژی نمونههای ارسالشده به بخش پاتولوژی بیمارستان شهید صدوقی یزد در سال 1393-1390
Bibliographic record
Abstract
چکیده زمینه و هدف: آزمایش پاپ اسمیر مؤثرترین و مناسبترین روش غربالگری جهت پیشگیری از سرطان دهانه رحم است و این تکنیک به علت شناسایی بیماری در مراحل اولیه تهاجمی سرطان رحم، باعث کاهش مرگومیر میشود. هدف از انجام این مطالعه، میزان تطابق نتایج تست پاپ اسمیر با نمونههای بیوپسی ارسالشده به بخش پاتولوژی بیمارستان شهید صدوقی است. مواد و روشها: در این مطالعه توصیفی تحلیلی، 145 نمونه سیتولوژی و پاتولوژی ارسالی به بخش پاتولوژی بیمارستان شهید صدوقی یزد انتخاب شدند. میزان تطابق بین نتایج تست پاپ اسمیر با پاتولوژی با استفاده از نرمافزار آماری SPSS و ضریب توافق رونوشت کاپا انجام شد. میزان P<0.01 ازنظر آماری معنیدار در نظر گرفته شد. یافتهها: بررسی میزان نتایج تست پاپ اسمیر با نتایج پاتولوژی نشان داد که توافق اندکی بین نتایج سیتولوژی با نتایج پاتولوژی وجود دارد (P<0.01, K:0.26). نتیجهگیری: با توجه به نتایج این مطالعه، اندک بودن میزان توافق بین نتایج تست پاپ اسمیر و نتایج پاتولوژی مشاهده شد. بنابراین برای بهبود بهتر کیفیت گزارشها سیتولوژیک، بهبود عملکرد ماماها، رزیدنتها و سیتولوژیستها توصیه میگردد. کلمات کلیدی: سرطان رحم؛ پاپ اسمیر؛ بیوپسی References - Aghajani D M, Shafigh E and Mohammadpour T R (2006) [Comparison of cervix brush with spatula ayres for obtaining endocervical cells]. 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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.162 | 0.113 |
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".