Bibliographic record
Abstract
Health care costs in general, and prescription drug costs in particular, are rapidly rising. Between 1996 and 2007 the average annual per capita health care cost is projected to increase from dollar 3,781 to dollar 7,100. [AQ1] The single leading component of health care cost is the cost of prescription drugs (currently 10% of total health care spending, projected to become 18% in 2008). The average cost per drug increased 40% during the 1993-1998 period. Forty-one million Americans have no health insurance, and those who have, have inadequate prescription drug coverage. [AQ2] To cope with this situation, many consumers are trying to economize by doing without the prescriptions or the appropriate doses, buying generics or medicines from Canada or Mexico, or splitting pills of higher doses to take advantage of the pricing policy of drug manufacturers. Some of these approaches are medically and/or legally acceptable, while some are dubious. Most adversely affected are the seniors and poor; for certain groups of seniors prescription drugs account for 30% of their health care spending. The problem must receive prompt concerted attention from consumers, insurers, pharmaceutical companies, and lawmakers before it gets out of hand.
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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".