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Record W336425302

Mapping China using MODIS data : Method, software and data products

2005· article· en· W336425302 on OpenAlexaff
Ronggao Liu, Jiyan Lui, Dafang Zhuang

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRemote sensingSoftwareSuiteCloud computingComputer scienceKey (lock)Data centerData processingEnvironmental scienceProduct (mathematics)Software suiteProcess (computing)DatabaseAlgorithmMeteorologyData miningGeologyGeographyMathematics
DOInot available

Abstract

fetched live from OpenAlex

2005 International Symposium on Environmental Mornitoring in East Asia -Remote Sensing and Forests-,Hosted The EMEA Project, Kanazawa University 21st=Century COE Program -Environmental Monitoring and Predicition of Long- and Short- Term Dynamics of Pan-Japan Sea Area- ,予稿集, EMEA 2005 in Kanazawa, 国際学術研究公開シンポジウム『東アジアの環境モニタリング』-リモートセンシングと森林-,年月日:200511月28日~29日, 場所:KKRホテル金沢, 金沢大学自然科学研究科, 主催:金沢大学EMEAプロジェクト, 共催:金沢大学21世紀COEプログラム「環日本海域の環境変動と長期・短期変動予測」

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.081
GPT teacher head0.303
Teacher spread0.222 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations3
Published2005
Admission routes1
Has abstractyes

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