Bibliographic record
Abstract
During development of the nervous system, cell migration, axonal outgrowth, axonal guidance, and selective cell adhesion and recognition are some of the crucial processes required for neural pattern formation. Numerous studies reveal that cells bind selectively to one another and that they segregate according to their tissue types. As early as 1907, Wilson demonstrated that dissociated cells from two different types of sponges, when mixed together, reassociated to form two organisms, each containing cells from one parent species. Similar results are also observed in coelenterates (Chalkey, 1945), chick embryonic cells (Moscona and Moscona, 1952) and amphibian embryonic cells (Holtfreter 1948a,b; Townes and Holtfreter, 1955). When the nervous system is in its developmental stages, neurons extend their axons over considerable distances to innervate their targets. Studies done in grasshopper (Bastiani et al, 1986; Bastiani and Goodman, 1986; du-Lac et al, 1986), zebrafish embryo (Kuwada, 1986,1992), and chick retinal ganglion cells (Silver and Sapiro, 1981) indicate that these connectivities are carried out in a highly stereospecific fashion. There are many theories regarding these selective interactions, and cell adhesion molecules have been shown to play a very significant role. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.037 |
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".