Bibliographic record
Abstract
Stuff. The ICUs are frequently strapped to provide necessary equipment for day-to-day operations. The sine qua non of critical care “stuff” is the mechanical ventilator. Most ICUs purchase or lease these to care for their usual patient needs. The number of available machines depends on the setting. Kaji and Rubinson found that 71% of hospitals in Los Angeles had less than 6 ventilators available for emergency use. Ontario reports having 16 ventilators/100 000 population. Challenges to surging these machines occur, in part, because vendors often have working supply relationships with multiple customers. Support from the Strategic National Stockpile can provide additional ventilators within 12 hours, providing states and transportation systems can deliver them to the affected facilities. However, it is important to note that in all of the planning for the delivery of emergency mass critical care with mechanical ventilation, no national support plans at present include the provision of medical gas, including oxygen. In this issue of the Journal of Intensive Care Medicine, Mahoney, Biffl, and Cioffi outline an ambitious plan for intensive care units (ICUs) to prepare for mass casualty incidents (MCIs). The journal’s dedication of article space to this topic should be applauded, for modern health care systems with expanding critical care services have insufficient specialized staff, medical equipment, and ICU space to provide standard critical care for the influx of additional patients from a disaster. Therefore, disaster planning, which has typically been under the purview of emergency medicine or more recently, public health disciplines, must transcend into critical care medicine. Additionally, the recent severe acute respiratory syndrome (SARS) epidemic and the looming threat of an influenza pandemic have stimulated much recent debate about how to care for a surge of critically ill who overwhelm ICUs beyond that normally seen in suddenimpact disasters. Therefore, intensivists and the health care systems in which they operate must heed the advice provided in the accompanying article and elsewhere to best prepare for an inevitable surge in critical care requirements. Although the accompanying article develops a methodology for developing a detailed disaster plan for ICUs, I think the planning process needs to consider Murphy’s Law as perhaps an alternative strategy in many ways.
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 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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".