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Record W2266131266

Probing for Avalanche Victims

2004· article· en· W2266131266 on OpenAlexaboutno aff
Henry Ballard, Dale Atkins, L.F. Ballard

Bibliographic record

VenueProceedings of the 2004 International Snow Science Workshop, Jackson Hole, Wyoming · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Computer scienceGridSearch and rescueLine (geometry)Artificial intelligenceOperations researchGeographyEngineeringMathematicsGeodesyGeometry
DOInot available

Abstract

fetched live from OpenAlex

Experience from avalanche rescues and rescue drills reveals that often the buried victim is not found on the first or even second pass of an organized probe line. Traditional probe spacing used in North America is based on assumptions and practice done nearly 40 years ago (Schild, 1963 and 1973). More recent work by Jamieson and Auger (1997) challenged those assumptions and presented evidence that the original probabilities of detection (POD) were high, but still their probe targets were not human shaped, and thus did not offer a realistic search target. We developed a computer program PROBE that simulates a fully articulated human body, “buries” the body, and then implements the probing technique specified by various command line options. The derived “bodies” offer realistic targets, and the program can compare the PODs for different probe-pole grid patterns. 10,000 trials were run for a variety of probegrid spacings, including the standard coarse probe, Canadian 3-holes-per-step, and European methods. Results suggest significantly lower PODs for the commonly used probe-grid patterns. Search and rescue leaders should reconsider their use of the traditional techniques. Some options are offered that may make searching more efficient, for the sake of the searchers and of the buried victim.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.241
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the 2004 International Snow Science Workshop, Jackson Hole, WyomingSame topicFire effects on ecosystemsFrench-language works237,207