Metacognitive confidence: A neuroscience approach
Bibliographic record
Abstract
Metacognition refers to thinking about our own thinking and implies a distinction between primary and secondary cognition. This article reviews how neuroscience has dealt with this distinction between first and second-order cognition, with special focus on meta-cognitive confidence. Meta-cognitive confidence is important because it affects whether people use their primary cognitions in guiding judgments and behaviors. The research described in this review is organized around the type of primary thoughts for which people have confidence, including judgments about memory, choices, and evaluative judgments. Along with other areas, prefrontal cortex and parietal regions have been consistently associated with judgments of meta-cognitive confidence in these three domains. Although metacognitive confidence might be associated with particular brain activity in most of the studies reviewed, confidence often seems to be confounded with other potentially important dimensions, such as effort and ease. Given that people tend to be less certain in tasks that are more difficult, more research is needed to examine the brain activity specifically linked to confidence.
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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 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".