A Logical Inquiry of Emotions and Cognition
Bibliographic record
Abstract
ABSTRACT Experimental procedures in neuroscience rely on the standpoints that the mind is a functional state of the brain and a clear subdivision among different mental faculties does exist in the cortex. According to cognitive neuroscientists, the term "mind" encompasses just the "cognitive" faculties, such as consciousness, perception, thinking, judgement, memory, leaving apart the "emotional" states. Here, taking into account the powerful tools of the first-order predicate logic, we evaluated whether: a) the mind is a function on the physical brain activity; b) different mental faculties can be reduced to a more general one; c) the division of mental faculties in cognition and emotion holds true. We demonstrated that nervous activity is equivalent to mental faculties and that emotions and cognition do not stand for two separated functions of the mind. This means that, counter to our common-sense belief, cognition and emotions are splitted and every faculty of the mind necessarily displays a counterpart in other ones. We point out how it is possible for condensed mind faculties to be unglued in order to become apparently different functions. Therefore, seemingly different mind faculties turn out to be equivalent, because the same logical framework holds for all the types of brain activities, independent of their boundaries and magnitude.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.021 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".