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Record W135829450

Development of an Operator-Machine Interface for ELVISS

2006· article· en· W135829450 on OpenAlexaboutno aff
Sharon McFadden, Jacquelyn M. Crébolder, Vincent Larochelle

Bibliographic record

VenueDefense Technical Information Center (DTIC) · 2006
Typearticle
Languageen
FieldMedicine
TopicOcular and Laser Science Research
Canadian institutionsnot available
Fundersnot available
KeywordsInterface (matter)Computer scienceOperator (biology)Process (computing)Real-time computingRemote sensingOperating systemGeography
DOInot available

Abstract

fetched live from OpenAlex

DRDC Valcartier has developed a multi-sensor surveillance system composed of an active imaging system (the Airborne Laser-Based Enhanced Detection and Observation System (ALBEDOS)) and a thermal Infrared (IR) imaging system. This system is called the Enhanced Low-light level Visible and Infrared Surveillance System (ELVISS). The purpose of the system is to enhance surveillance capability at night and under degraded weather conditions especially for Search and Rescue (SAR) operations. Throughout the development process, DRDC Toronto was responsible for the design of the Operator-Machine Interface (OMI) for ELVISS. This report summarizes the development of the OMI carried out under Work Unit 13da22, Operator Machine Interface (OMI) for ELVISS. The emphasis is on ELVISS' current state and includes recommendations for research and development that would further enhance the ability of the system to support SAR operations.

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)0.001
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.025
GPT teacher head0.331
Teacher spread0.306 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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