Analysis of chemotaxis when the fraction of responsive cells is small - application to mammalian sperm guidance
Bibliographic record
Abstract
The detection of chemotaxis-related changes in the swimming behavior of mammalian spermatozoa in a spatial chemoattractant gradient has hitherto been an intractable problem. The difficulty is that the fraction of responsive cells in the sperm population is very small and that the large majority of the cells, though non-responsive, are motile too. Assessment of the chemotactic effects in a spatial gradient is also very sensitive to the quality of sperm tracking. To overcome these difficulties we propose a new approach, based on the analysis of the distribution of instantaneous directionality angles made by spermatozoa in a spatial gradient versus a no-gradient control. Although the use of this parameter does not allow identification of individual responding cells, it is a reliable measure of directionality, independent of errors in cell tracking caused by cell collisions, track crossings, and track splitting. The analysis identifies bias in the swimming direction of a population relative to the gradient direction. It involves statistical chi2 tests of the very large sample of measured angles, where the critical chi2 values are adjusted to the sample size by the bootstrapping procedure. The combination of the newly measured parameter and the special analysis provides a highly sensitive method for the detection of a chemotactic response, even a very small one.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".