Bibliographic record
Abstract
Touch is the earliest sensory modality the infant relies on, and is crucial for the first months of life and for survival. The other sensory modalities (taste, smell, vision, and hearing) become active later. Smell and taste are also critical in helping the infant identify the mother and, later, other caregivers and helpers. The study and analysis of the infant’s central nervous system (CNS) is simpler and is easier to model and explore. One of the primary functions of the newly born seems to be the exploration of self, mother, and (gradually) other objects in the environment. This paper deals with the slow process of exploration, identification and the development of self and object in the CNS. Although crude, the model allows a description and understanding of the processes of early merging, splitting, and denial of attributes of the self and object as psychological attributes.  The paper should motivate development of theoretical, computational and experimental models for the study of natural neural systems in the process of growth, maturity, and functional versatility. It should lead to formulations of redundant systems, growth of physical size, and functional properties of the CNS. No experiments were conducted to validate the model. Physiological, neural and experimental efforts are needed that would confirm, improve, refute, or complement the model.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".