MétaCan
Menu
Back to cohort
Record W2165545409 · doi:10.1109/igarss.2012.6350796

Caribbean Satellite Disaster Pilot: A CEOS activity for GEO in support of GEOSS

2012· article· en· W2165545409 on OpenAlexaffabout
Nicole Alleyne, Andrew Eddy, Stuart Frye, Jean-Francois Saulnier, Guy Aubé, Guy Séguin, Pat Capellaere, Dan Mandl

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsAgency (philosophy)SatelliteEmergency managementWork (physics)Earth observationGeographyAction planMeteorologyPlan (archaeology)On boardAeronauticsEnvironmental resource managementPolitical scienceRemote sensingEngineeringManagementEnvironmental scienceArchaeologySociology

Abstract

fetched live from OpenAlex

The Caribbean Satellite Disaster Pilot (CSDP) was established in 2009 under the Group on Earth Observations (GEO) 2009-2011 work plan. It was implemented through the Committee on Earth Observation Satellites (CEOS) 2009-2011 Action Plan under USA National Aeronautics and Space Administration (NASA) leadership with strong support from the Caribbean Disaster and Emergency Management Agency (CDEMA), the Canadian Space Agency (CSA), the Caribbean Institute for Meteorology and Hydrology (CIMH) the Water Center for the Humid Tropics of Central America and the Caribbean (CATHALAC), and the University of West Indies (UWI). It aims to demonstrate the effectiveness of satellite data for full cycle disaster management by identifying and implementing specific applications and products and addressing endemic training and capacity building issues in the region. The project is entering the final year of its demonstration phase before beginning operational implementation of its key services in 2013.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.037
GPT teacher head0.293
Teacher spread0.256 · 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 designSimulation or modeling
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

Citations1
Published2012
Admission routes2
Has abstractyes

Explore more

Same topicReservoir Engineering and Simulation MethodsFrench-language works237,207