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Record W4381333664 · doi:10.3897/jbgs.2018.39.16

Simple queries - Simple answers. First steps in the spatial databases

2018· article· bg· W4381333664 on OpenAlexaff
Sofia Kostadinova, Б. Н. Марков, Н. Н. Петров

Bibliographic record

VenueJournal of the Bulgarian Geographical Society · 2018
Typearticle
Languagebg
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsTransport Canada
Fundersnot available
KeywordsSimple (philosophy)Computer scienceInformation retrievalDatabase

Abstract

fetched live from OpenAlex

Все по-голямото прилагане на географските информационни системи води до натрупване на информация, която налага нейната систематизация и подредба във вид подходящ за многократно ползване. Пространствените бази данни са мощен инструмент, който освен съхранение на данните в подреден вид, позволява различни потребители да извличат информация полезна за взимането на решенияи решаване на проблеми, планиране и др.

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)0.010
metaresearch head score (Gemma)0.047
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: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.047
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.005
Science and technology studies0.0030.003
Scholarly communication0.0100.020
Open science0.0040.010
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0620.028

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 head0.249
Teacher spread0.232 · 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
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueJournal of the Bulgarian Geographical SocietySame topic3D Modeling in Geospatial ApplicationsFrench-language works237,207