MétaCan
Menu
Back to cohort
Record W2010367195 · doi:10.2202/1547-7355.1422

Canine Remote Deployment System for Urban Search and Rescue

2008· article· en· W2010367195 on OpenAlexaff
Alexander Ferworn, Devin Ostrom, Kevin Barnum, Mike Dallaire, Denis Harkness, Mike Dolderman

Bibliographic record

VenueJournal of Homeland Security and Emergency Management · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsGovernment of OntarioToronto Metropolitan University
Fundersnot available
KeywordsSoftware deploymentRubbleSearch and rescueComputer securityMechanism (biology)Computer scienceSystems engineeringEngineeringCivil engineeringSoftware engineeringPhysics

Abstract

fetched live from OpenAlex

The Canine Remote Deployment System (CRDS) is a dog-mounted remote delivery system for patients trapped in rubble when human contact is precluded but access by disaster dogs is possible. The system is capable of deploying items to the trapped individual by placing them in a pouch—called an "underdog"—attached to the release mechanism. This paper describes the device, how it works, how it has been used and how it might be employed in future disasters.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: Other design
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0420.017

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 head0.023
GPT teacher head0.312
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations20
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Homeland Security and Emergency ManagementSame topicHuman-Animal Interaction StudiesFrench-language works237,207