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Spatial Assessment of Pre-20th-century Settlements on Failaka Island, Kuwait: An Analytical Study Based on GIS and GPS

2011· article· en· W2606591475 on OpenAlexvenueno aff
Mohamed Alkhuzamy Aziz, Ajeel Al-Zaher, Obaid AlOtaibi

Bibliographic record

VenueArab world geographer · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHuman settlementSettlement (finance)GeographyGlobal Positioning SystemDocumentationGeographic information systemArchaeologyCartographyEngineeringComputer science

Abstract

fetched live from OpenAlex

The present study applies historical induction using historical geographic surveys and archaeological documentation, in addition to analytical positioning, in which positioning criteria are matched with historical studies and archaeological documents to define the locations of urban and demographic settlements on Failaka Island during the successive periods in which various civilizations settled there. This research relies on the use of a geographic information system (GIS) and a global positioning system (GPS) for the spatial positioning of settlements on maps through the projection of historical studies, archaeological documents, and field surveys, including interviews with historians and leading families among Failaka Island's inhabitants. The importance of this study lies in the applications of these modern technologies to the historical documentation of the demographic presence of settlement on Failaka Island, one of the most interesting sites of settlement in the Arab world because of the dearth of ...

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.089
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.272
Teacher spread0.238 · 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 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
Published2011
Admission routes1
Has abstractyes

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