Bibliographic record
Abstract
Abstract All cells maintain a voltage across their plasma membranes. Only excitable cells, however, can generate action potentials, the rapid, transient changes in membrane potential that spread along the surface of these unique cells. Action potential generation and propagation occurs through, and is regulated by, the function of voltage‐gated ion channels – proteins with ion‐selective pores that span the cell membrane. Ion channels undergo changes in their structural conformation in response to changes in the electrical field across the membrane. These structural changes cause the opening of pores – channels – through which ions can flow down their electrochemical gradient. The charge carried by ions creates an electrical current and rapidly alters the membrane potential with time‐ and voltage‐dependent properties. This rapid, transient membrane potential change is called the action potential. Action potentials transmit information within neurons, trigger contractions within muscle cells, and lead to exocytosis in secretory cells. Key Concepts: All cells maintain a voltage difference across their plasma membranes. Action potentials are all‐or‐nothing, transient changes in membrane potentials of electrically excitable cells that carry important cellular information. Influx of sodium ions through voltage‐gated sodium channels is responsible for the upstroke of the action potential, whereas efflux of potassium ions through voltage‐gated potassium channels is responsible for the falling phase. Propagation of action potentials depends on gating kinetics of ion channels and intracellular and membrane resistances.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
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".