Bibliographic record
Abstract
Body ownership is a complicated and multifaceted percept. Although we subjectively perceive body ownership to be a stable component of our identity, recent work has illustrated that body ownership is a dynamic construct that is constantly updated by the integration of current endogenous and exogenous body-related information. The goal of this study was to explore the relation between these endogenous (interoceptive) and exogenous (exteroceptive) channels of information. We investigated this by using a heartbeat perception (HBP) task to measure interoceptive accuracy, and the Rubber Hand Illusion (RHI) to measure malleability of body ownership. Based on prior findings, we hypothesized that the less accurate you are at counting your heartbeats, the more susceptible you will be to the RHI (i.e. the more malleable your sense of body ownership will be). In addition, we were also interested in exploring the relationship between interoception and emotion recognition ability (ERA). In this experiment, we failed to induce the RHI, and thus could not investigate the relationship between endogenous and exogenous body-related information. However, we successfully demonstrated the reliability of the interoceptive accuracy HBP task, as well as demonstrated that interoceptive accuracy is not related to ERA.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".