Formal Descriptions of Cognitive Processes of Perceptions on Spatiality, Time, and Motion
Bibliographic record
Abstract
Recent researches in both cognitive informatics and computational intelligence are interested in the human perceptual senses of spatiality, time, and motion, which are fundamental cognitive life functions according to the Layered Reference Model of the Brain (LRMB). This paper presents the cognitive process of human perceptual senses on spatiality, time, and motion. The sense of spatiality is investigated into the coordinate system, orientations, and cognitive maps, followed by the development of the mathematical model and the cognitive process of human spatial senses. The sense of time with the biological clocks, cognitive clocks, and their mathematical models are analyzed in order to explain the cognitive process of human time sense. On the basis of the formal models of senses of spatiality and time, the sense of motion is modeled as a complex sense incorporating both of spatiality and time. Then, the cognitive, mathematical, and process models of the sense of motion are rigorously established. This work provides a theoretical framework for the rigorous implementation of the intelligent behaviors of cognitive computers, autonomous agent systems, and robots in cognitive informatics and computational intelligence.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".