Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Clinical accounts of the effects of damage to orbitofrontal cortex (OFC) have provided important clues about the functions of this region in humans. Patients with OFC injury can demonstrate relatively isolated difficulties with decision making, and the development of laboratory tasks that captured these difficulties was an important advance. However, much of the work to date has been limited by the use of a single, complex decision-making task and by a narrow focus on risky decisions. A fuller understanding of the neural basis of decision making requires identification of the simpler components that underlie this complex behavior. Here, I review evidence that OFC lesions disrupt reversal learning in humans, as in animals, and show that this deficit in reversal learning is an important mechanism underlying the difficulties of such patients in the Iowa gambling task. Reversal learning, in turn, can be decomposed into simpler processes: a failure to rapidly learn from negative feedback may be the critical difficulty for OFC patients. OFC damage can also affect forms of decision making that do not require trial-by-trial learning. Preference judgment is a simple form of decision making that requires comparing the relative value of options. Humans with OFC lesions are more inconsistent in their choices, even in very simple preference judgment tasks. These results are broadly consistent with the view that OFC is critically involved in representing the relative value of stimuli, but also raise the possibility that this region plays distinct roles in reinforcement learning and value-based judgment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it