A new paradigm for muscle contraction
Bibliographic record
Abstract
Muscle contraction has fascinated lay people and scientists for centuries. However, a good understanding of how muscle contraction occurs seemed only possible once microscopy techniques had evolved to a level where basic structural features, such as the regular cross striation patterns of fibers, could be observed in the late 19th century. In the early 20th century, a stimulated muscle was simply considered a new elastic body (Gasser and Hill,1924). Shortening and work production took place with a fixed amount of energy tha twas stored in this body and evolved elastically through stimulation. However, this notion was proven false when Wallace Fenn demonstrated that muscle produced an increasing amount of total energy when increasing its mechanical work output; an observation that was in contradiction with Hill’s elastic body theory (Fenn, 1923,1924). Specifically, Fenn, who worked in the laboratory of Hill and measured heat and work production in frog muscles, found that a muscle allowed to shorten liberated more energy than a muscle held isometrically or a muscle that was stretched. This has become known as the Fenn effect in muscle physiology.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.020 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".