The Use of Modified Cunningham Chambers for the Enumeration of H Rosettes, E Rosettes, and Lymphocyte-Tumour Cell Conjugates
Bibliographic record
Abstract
In this paper, we have described the use of a slide-coverslip Cunningham chamber which is ideal for counting delicate rosettes and lymphocyte-tumour cell conjugates. The ease of construction, facility of use, and economy of cost in comparison with hemocytometers make the use of these chambers the method of choice for rosette counts in general. In contrast to standard double-slide Cunningham chambers, the design of these rosette chambers is such that they can be used with ordinary light microscope objectives (including oil immersion), they can be more easily loaded without trapping air bubbles, and they can be sealed without tilting the slide. As an example of one potential application of these chambers to tumour immunology, data have been presented showing the high proportion of lymphocyte-tumour cell conjugates which can be formed by human peripheral blood cells. The ability of any particular tumour cell to form conjugates did not necessarily reflect the susceptibility of that cell type to natural killer (NK) cell-mediated lysis, nor was there any evidence that E rosette-forming cells preferentially formed conjugate in comparison to non E rosette-forming cells.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".