“Cold Card” to Guide Responders in the Assessment and Care of Cold-Exposed Patients
Bibliographic record
Abstract
INTRODUCTION: A concise, easy-to-use decision aid "Cold Card" that can be carried in the field by wilderness search and rescue teams or medical responders to advise on assessment and care of cold-exposed patients was created. METHODS: A 2-sided card was designed to summarize the important principles established by the Wilderness Medical Society practice guidelines for hypothermia. The card was continually updated through feedback from several content experts. The card was then distributed for further feedback from members of the Search and Rescue Volunteer Association of Canada and enrollees of the Baby It's Cold Outside web-based educational program. This additional feedback was used to create the final iteration of the card. RESULTS: On the front "ASSESS COLD PATIENT" side, the level of cold exposure or hypothermia is accomplished by evaluating (as either normal or impaired function) consciousness, movement, shivering, and alertness on a series of concentric rings. The important treatment actions are provided for each cold-exposure level. The back "CARE FOR COLD PATIENT" side provides the required elements and principles of use for a hypothermia wrap. The Cold Card is available for free download and unlimited use for education or in-field instruction by any individual or group. The card should be printed on heavy, waterproof stock (13×18 cm) for use in all weather conditions. CONCLUSIONS: Key elements of hypothermia evaluation and field care have been summarized on a small portable card for laypersons, trained rescuers, and first responders.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.030 |
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".