Automated dual olfactory device for studying head/tail chemosensation in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
The correct interpretation of threat and reward is important for animal survival. Often, the decisions underlying these behavioral programs are mediated by volatile compounds in the animal's environment, which they detect and discriminate with specialized olfactory neurons along their body. Caenorhabditis (C.) elegans senses chemical stimuli with neurons located in the head and the tail of the animal, which mediate either attractive or aversive behaviors. How conflicting stimuli are processed in animals navigating different chemical gradients is poorly understood. Here, we conceived, created, and capitalized on a novel microfluidic device to enable automated and precise stimulation of head and tail neurons, either simultaneously or sequentially, while reading out neuronal activity in sensory and interneurons using genetically encoded calcium indicators. We achieve robust and programmable chemical pulses through the modulation of inlet pressures. To evaluate the device performance, we synchronized the flow control with microscopy data acquisition and characterized the flow properties in the fabricated devices. Together, our design has the potential to provide insight into the neural circuits and behavior of C. elegans simulating the experience of natural environments.
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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 | 0.000 | 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) | 0.001 | 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 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".