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Record W2789560930

Remote sensing data and their use in topoclimatic study

2018· article· en· W2789560930 on OpenAlexaboutno aff
Miroslav Vysoudil

Bibliographic record

VenueUniversity of Maribor digital library (University of Maribor) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)Raster graphicsComputer scienceRemote sensingData centerRaster dataWork (physics)Land coverData collectionSpatial analysisData scienceEnvironmental resource managementGeographyLand useEnvironmental scienceArtificial intelligenceCivil engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

This work demonstrates the potential of using current digital satellite raster data to study a topoclimate. Also presented are digital vector data. All data have been provided by the Canadian Center for Remote Sensing in Ottawa within the scope of the solution for the project titled “Environmental Consequences of Local Climatic Effects” (A Case Study: British Columbia). The model region represents the southwest part of British Columbia located between Vancouver and the Okanagan basin. The most valuable components of a topoclimatic research are altimetric data assisting in the calculation of a DEM, multi-spectral images assigned to appropriate land cover categories, and thermal images. Subsequent integration of the DPZ and vector data provides a powerful tool for solving tasks leading to a topoclimate description, potential climatic effects and in wider implications even for studies of their impacts on the living environment.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.004
Open science0.0010.003
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 head0.014
GPT teacher head0.163
Teacher spread0.149 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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