Bibliographic record
Abstract
Although several decades of studies have detailed peripheral and ascending nociceptive pathways to the thalamus and cerebral cortex, pain is a symptom that has remained difficult to characterize anatomically and physiologically. Positron emission tomography (PET) and functional magnetic imaging (fMRI) have recently demonstrated a number of cerebral and brain stem loci responding to cutaneous noxious stimuli. However, intersubject variability, both in the frequency and increased or decreased intensity of the responses, has caused uncertainty as to their significance. Nevertheless, the large number of available imaging studies have shown that many areas with recognized functions are frequently affected by painful stimuli. With this evidence and recent developments in tracing central nervous system connections between areas responding to noxious stimuli, it is possible to identify nociceptive pathways that are within, or contribute to, afferent spino-thalamo-cortical sensory and efferent skeletomotor and autonomic motor systems. In this study it is proposed that cortical and nuclear mechanisms for pain perception and response are hierarchically arranged with the prefrontal cortex at its highest level. Nevertheless, all components make particular contributions without which certain nociceptive failures can occur, as in pathological pain arising in some cases of nervous system injury.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".