Bibliographic record
Abstract
We all know the flu season is soon to be upon us. The main question is how serious will it be? The World Health Organization (WHO) has declared a pandemic already and expects an explosion in the number of deaths worldwide. The lay press is rife with concern. A Google search for swine and H1N1 flu results in about 200 million hits. PubMed and other databases with strictly medical interests show more than 800 references published this year. Google has actually partnered with the Public Library of Science to premiere a new website that will allow researchers to immediately share their findings and ideas about the H1N1 virus with the scientific community at large. Every day, I read an article in my newspaper at the breakfast table. It was with great interest that last week I read an article in which my province’s health minister stated there was no need to worry about the health risk and that current measures in place were more than enough to deal with the new flu season. This worried me both as a physician and as a potential patient because I was aware that at one time this year, Quebec was actually the second most dangerous place in the world to catch the H1N1 flu, with a mortality rate second only to Mexico. Ours is not the only health minister facing a possible pandemic who may have difficulty both preparing the populace and ensuring health care delivery. No health minister in Canada has served a full term in the health post, and the longest serving health minister has been in the post for only 3 years. The federal health minister is also largely untested. How is this going to affect the surgeon? Apparently it will touch us in many ways, particularly if the new season brings a more virulent strain, as the WHO expects. Currently, the replication and case fatality rate are lower than that of the Spanish flu of 1918, but we have no idea how changes in the virus will affect its behaviour in the coming year. Even slightly increased rates of either its ability to infect or kill are going to make this a difficult flu season. Resources will be limited for surgeons for a number of reasons. Intensive care unit beds will be occupied with flu victims. Respirators will be at a premium as new strains are expected to attack mainly the respiratory system in young patients. Some provinces are trying to work out selection criteria for being on or staying on a respirator if we need to make room for the flu victims. This type of ethical decision process over who lives and dies would usually take months or years to determine; we need to figure it out in the next few weeks. With the crush of patients in the emergency departments, there may be a shortage of hospital workers, including physicians and nurses. I assume most physicians with young children at home will not be going to work without some deep soul-searching. But of equal importance to patient care is the ancillary hospital staff. There will be little means for the hospital administration to force staff to stay on the job. Absenteeism in the whole health care sector will be difficult to correct. Not only will we lose the people who are worried about their families, those who are infected or those caring for a family member who is infected will also be missing in action. The provincial ministers have thought of ways to ensure care for the patients. Some have proposed reimbursement packages up to $500 per hour, whereas others are considering legislation resembling inscription. All these factors will obviously put elective surgical procedures on the back burner for a number of months until immunization is prepared. Surgeons will obviously be hard-hit financially if no surgeries are being performed. However, there is still a need for surgeries to occur. There are the obligatory surgical cases that never go away: trauma, cancer, infection, acute abdomens and so on. What have the provincial mavens planned to ensure these patients continue to receive care? There seem to be no plans that designate surgical emergent hospitals to ensure that flu patients do not encroach on the treatment of other patients. By the time this edition goes to press, I hope the provincial ministers have proven me wrong.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.229 | 0.135 |
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".