Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multisensory integration (MSI) is a crucial process by which organisms combine information from multiple senses to enhance their perception and adapt to the environment. This review focuses on MSI in Drosophila, an ideal model organism due to its well-characterized neural circuitry and genetic tractability. We first describe the five main sensory modalities (vision, olfaction, gustation, mechanosensation, and thermosensation) and how they contribute to the Drosophila’s behavior. Then, we discuss the basic models of MSI, including feedback, convergence, gating, parallelism, and association. The underlying neural circuits involved in MSI, such as those related to foraging, navigation, and feeding behaviors, are also explored. Additionally, we highlight the role of neuromodulators in regulating MSI and its functional significance in enhancing information acquisition and decision-making. Overall, understanding MSI in Drosophila provides valuable insights into the mechanisms underlying complex behaviors and serves as a foundation for further studies in other organisms, ultimately helping us better understand how the nervous system processes and integrates multisensory information.
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.
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 | 0.000 | 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 it