Bibliographic record
Abstract
Movement is an essential characteristic of life. On the cellular level, it is powered by many different classes of motor proteins. Kinesins are one class of linear molecular motor proteins, which move on cytoskeletal tracks called microtubules. Conventional kinesins are dimeric molecules composed of several domains, including a motor domain which has a catalytic core that binds to a nucleotide (ATP or ADP). The nucleotide-bound state of kinesin during the motile cycle affects its neck position, a determinant of its direction of movement, and microtubule affinity. There are two types of motor protein movement: processive, in which the motor steps progressively along the cytoskeletal track without detaching, and nonprocessive, in which the motor detaches from the track after a single power stroke. Conventional kinesins move processively due to the dimerization of the two motor heads. The two heads are kept out of phase due to communication between the heads. Kar3, the kinesin of interest in this project, moves non-processively and is the only C-terminal motor protein found in budding yeast. Its functional form is a heterodimer with one of two non-catalytic polypeptides, Cik1 and Vik1. This project showcases Vik1 as the key to a novel model for motility due to the surprising discovery that the Vik1:microtubule interaction is influenced by the nucleotide-binding state of Kar3. There must be communication between Kar3 and Vik1 to cause Vik1’s release from the microtubule, as well as to allow the progression of microtubule-binding and, thus, movement along the microtubule.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".