Fixation Techniques for Fine Needle Aspiration Biopsy Smears Prepared Off Site
Bibliographic record
Abstract
OBJECTIVE: To identify a simple, cost-effective, reliable fixation method for fine needle aspiration biopsy (FNAB) yielding a specimen suitable for mail transport. STUDY DESIGN: Smears prepared from 59 FNABs of surgical specimens were fixed by continuous fixation in 95% ethanol, spray fixation, air drying, ethanol fixation for either 5 minutes or 4 hours followed by spray fixation, or fixation in 95% ethanol for either 30 minutes or 4 hours followed by air drying. Fixation was graded as unsatisfactory, suboptimal, average, good or excellent. RESULTS: Of smears continuously fixed in ethanol, 96.6% were graded as excellent. Of smears fixed in ethanol followed by spray fixation, 93.2% were excellent irrespective of fixation time; 64.4% of spray-fixed smears were excellent and 27.1% good. Of air dried smears, 93.2% were unsatisfactory or suboptimal; 83.0% of smears fixed in ethanol for 30 minutes and 74.6% of smears fixed for 4 hours prior to air drying were unsatisfactory or suboptimal. CONCLUSION: Fixation of smears in 95% ethanol followed by spray fixation produces excellent results, comparable to those with continuous fixation in ethanol. Spray fixation is generally good but not consistently excellent. Air drying or fixation in ethanol followed by air drying yields unsatisfactory or suboptimal results in most cases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".