MétaCan
Menu
Back to cohort
Record W2388425332

Design and Application of Tarim Desertification Monitoring and Early Warning System

2013· article· en· W2388425332 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Technology and Development · 2013
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer scienceWarning systemEarly warning systemWatershedDesertificationField (mathematics)Tarim riverTarim basinData collectionData miningGeologyGroundwaterMachine learningTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

To meet the urgent needs of desertification monitoring in the Tarim River watershed,it established desertification and model databases for the early warning monitoring system and WEBGIS in the study area based on an integrated framework of the VB+SuperMap Objects(C/S) and the c#+SuperMap IS.NET(B/S).By using the observed data and the prediction model for early warning,the results showed that around 90% prediction accuracy could be achieved.The proposed system can provide an efficient storage and organization for multivariate GIS data in relational database,and the real time monitoring system of the field sand collection could improve the performance of the system.The proposed system is originally developed for the downstream of the Tarim River watershed.Due to the univer sality,the system can support decision making for related government departments and researchers,and has played an important role in practice.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.350

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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