Recommendations of the American Diabetes Association and Summary of the Joint National Committee (JNC) - V and WHO/International Society of Hypertension (ISH) Special Reports
Bibliographic record
Abstract
Hypertension is one of those fields in medicine about which there are regular reports from committees describing guidelines on evaluation and treatment. Although many physicians express mixed feelings about committee reports, the range of choices available for treatment and the magnitude of the healthcare problem makes these consensus statements a valuable source of information. In 1993, the two most widely cited consensus reports were updated. The 1993 Joint National Committee on the Detection, Evaluation, and Treatment of High Blood Pressure [1] was the fifth such meeting in the United States (JNC-V). As was the case for the previous meetings, the Committee’s efforts are supported by US federal funds, and all of its members reside in the United States. The World Health Organization/International Society of Hypertension (WHO/ISH) Subcommittee [2] is selected by those two organizations and is largely European, although this committee report also reflects American and Canadian views, as well as views of two members of the Japanese Hypertension Society. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.021 |
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".