Bibliographic record
Abstract
The treatment of severe pain in Canada should be followed To the editor: H.W. Striebel in his book "Therapy of chronic pain" wrote: "We all can be excused if we cannot cure a patient, but not if we don't try to relieve suffering and pain.The epitaph of the ancient medical doctor Galenos was: "Divinum est sedare dolorem."(Relieving pain is a labor of God).In the figure below are shown the trends in morphine use, still considered a standard in the opioid analgesics group.Countries were chosen as top consumption leaders (Canada, USA), as well as their historic connections.The Czechoslovakia was one state between 1918 and 1993 and Slovakia was until 1918 a part of the Hungarian kingdom.Differences in trends beween countries are very clear.Some may say that this is only consumption of morphine, that differences in analgesic use may arise because alternative analgesics are preferred.However e.g. according to the INCB yearbook 2009 Canada and USA were in the 1 st and 2 nd place wrt consumption of oxycodone worldwide, and the situation is similar for use of fentanyl (2 nd and 6 th place worldwide resp.).In contrast our countries (Czech republic, Slovakia and Hungary) were in the 24 th , 23 rd and 22 nd place resp.for fentanyl consumption and in the 19 th , 30 th and 37 th place for oxycodone consumption worlwide.Variations in medical training, regulatory requirements and drug pricing can stimulate different prescribing decisions.The data from the Slovak State Institute for Drug Control were used in my observation and I have calculated the percentage of these strong opioids on the whole consumption of opioid analgesics (ATC group N02A).In the year 2000 morphine constituted in Slovakia 6.5%, fentanyl 6% and oxycodone was not available.In the year 2009 the situation was different.Morphine constituted only 1%, fentanyl more than 17% and oxycodone 11%the shift to other opioids is clear.In our previously published manuscripts we brought this problem to attention and we can still say that espe-
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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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.051 | 0.042 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".