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Record W3163024691 · doi:10.26389/ajsrp.f060217

Remote sensing and Geographic Information System (GIS) applications in transport geography studies

2017· article· en· W3163024691 on OpenAlexaboutno aff
Jamila Omar Ibrahim Mada Fakhruddin Ahmed Abdullah Mohammed Fakhruddin Ahmed Abdullah Mohammed

Bibliographic record

Venueمجلة العلوم الهندسية و تكنولوجيا المعلومات · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsGeographic information systemWork (physics)GeographyScale (ratio)Information systemGIS and public healthRemote sensingData scienceEnvironmental planningComputer scienceEnvironmental resource managementCartographyEngineeringEnvironmental science

Abstract

fetched live from OpenAlex

This study is to determine the learning outcomes programs of remote sensing and geographic information systems, and their role in job opportunity and work markets in Kingdom of Saudi Arabia, globally (Canada), The study illustrated the top five skills which required for success in professional life majoring in geographic information systems and mentioned by Environmental Systems Research Institute (ESRI), USA. The study deal with descriptive, analytical and comparative approaches. The study recommended the top five skills that required succeeding in Remote sensing and GIS" career, which recommended by Environmental Systems Research Institute, as the main scale to determine learning outcomes of remote sensing and geographic information system in Kingdom of Saudi Arabia and Arab world and then to identify the activities, skills and courses (i.e., the number of theoretical and practical hours, teaching methods, and laboratories ...), which are taught in these programs.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.303
Teacher spread0.278 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueمجلة العلوم الهندسية و تكنولوجيا المعلوماتSame topicSocioeconomic Development in MENAFrench-language works237,207