Bibliographic record
Abstract
UNLABELLED: Perceiving a body is a phenomenal experience completely different from experiencing a body as one's own body. Visual presentation of bodies or body parts recruits several occipitotemporal regions in the brain. Are these activations sufficient in order to change the phenomenal status of a body in one's own body? In this paper, I will review consolidated experimental evidence showing that the feeling of owning a body is not limited to the vision of a body, rather it is the result of a complex interaction between interoception, exteroception, and pre-existing body templates. To illustrate this complex interplay, I will take advantage of the so-called bodily illusions, referring to controlled illusory generation of unusual bodily feeling. These feelings include having a supernumerary limb, or lacking an arm, or feeling like you do not really have a body, or feeling that you do not really control a certain part of your body, or that your body is not really yours. In the last 15 years more than 150 empirical studies on body illusions have been published ( SOURCE: Pubmed, June 2014). These studies, using different technologies, are largely responsible for contributed our current understanding of bodily self-consciousness. WIREs Cogn Sci 2014, 5:551-560. doi: 10.1002/wcs.1309 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".