Bibliographic record
Abstract
This year’s Nobel Prize in Chemistry recognized the groundbreaking discovery of an important family of cellular receptors. It was Robert Lefkowitz and Brian Kobilka’s decades-long molecular dissections that deciphered the exciting mystery of how cells sense their environment1. Along their journey was a crucial milestone: the pinpointing of architectural parallels between the beta-adrenergic receptor and rhodopsin, the light-detecting receptor in the retina. That same revelation literally opened the scientific community’s eyes to a group of proteins that mediate innumerable functions in the human body. The pathobiological understanding of a plethora of medical conditions has greatly advanced since these receptors, the G-protein coupled receptors (GPCR), were identified. Now, it might be time for a common albeit historically underappreciated disorder to gain some benefits. Fibromyalgia syndrome (FM), an often-debilitating chronic pain syndrome, remains largely idiopathic. With its widespread nonarticular musculoskeletal pain and generalized tenderness, it is a diagnosis made when no tracing of structural or inflammatory process is present2. While FM has eluded clear etiological understanding for decades, its hallmark alteration in sensitivity to painful stimuli has been the target of meticulous investigation3,4. Enhanced central processing of pain has been implicated as the predominant mechanism, with correlations at the functional imaging level5. The … Address correspondence to Dr. Ablin; E-mail: jacob{at}post.tau.ac.il
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".