Neuron On, Neuron Off; Delineating between Degeneration or Evolutionary Adaptation?
Bibliographic record
Abstract
My podcast focuses on katydid neural impulses in response to ultrasonic bat calls and how they correlate. While anti-predator behaviour contributes to the survival aspect of fitness, it can come at the cost of reproductive success. Neoconocephalus ensiger is a species of katydid that resides in Southern Canada and the Northern United States from late summer to the first killing frost of the year. Neoconocephalus ensiger is infamous for having loud mating calls in the last months of the summer. Neoconocephalus ensiger has an auditory interneuron called TN1. When Neoconocephalus ensiger hears ultrasonic audio patterns that resemble echolocation calls of predatory bat species, TN1 is activated and the katydid ceases calling, since danger is present. At the start of the breeding season, Neoconocephalus ensiger calls at a low rate, but by the end of the season, they call often. There is confusion as to whether this difference is due to Neoconocephalus ensiger simply seeking to maximize their breeding before the season ends, employing an all-or-nothing reproductive strategy, or if their TN1 interneuron degenerates by the end of the breeding season, thus preventing them from detecting bat echolocation calls. Measuring the action potentials of the TN1 interneuron of katydids in response to ultrasonic echolocation calls can be used to determine whether or not they are still able to hear the echolocation calls at the end of the breeding season. Analyzing the acoustic recordings alongside neurophysiological recordings of the action potentials of the TN1 interneuron suggests that katydids are still able to hear the ultrasonic calls by the end of the season, thus engaging in more mating calls to maximize reproductive success.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".