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
Growth hormone (GH) is a powerful anabolic hormone with a broad spectrum of action that has been assessed with three general parameters: auxological to assess the growth response; biochemical to measure anabolic effects; and body composition. In childhood, linear growth response is assessed with height, short-term changes in height velocity (HV), and attainment of final adult height, which may not be concordant. In both children and adults, the biochemical indices utilized to predict and/or monitor response to GH therapy have included: (1) nonspecific indices: glucose, insulin, urea, protein synthesis, lipid metabolism, and lipoproteins; (2) more specific indices of the GH-IGF axis: GH binding protein, IGF-I, IGFBP-3, and acid-labile subunit; or (3) indices of bone and mineral metabolism: calcium, phosphate, bone alkaline phosphatase, osteocalcin, propeptides of procollagen type I and III, and bone mineral content. For body composition, body mass index, total body % fat, total body or extracellular water, and bone mineral density have been addressed most frequently. Modest changes with wide variability have been observed with most measurements. GH dose is a very significant positive factor for all parameters. Few of the currently available tests can reliably predict and/or monitor response to GH therapy. Of these, serum IGF-I appears to offer the best integrated indicator of the action of GH throughout all age groups.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it