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Record W4415071088 · doi:10.69714/hn4nxd21

RANCANG  BANGUN SISTEM INFORMASI GEOGRAFIS (SIG) OBJEK ARKEOLOGI BERBASIS WEB PADA MUSEUM BLAMBANGAN  KABUPATEN BANYUWANGI

2025· article· en· W4415071088 on OpenAlexaff
Rina Utari, Muhasshanah Muhasshanah, Bayu Ari Wibowo

Bibliographic record

VenueJurnal Riset Teknik Komputer · 2025
Typearticle
Languageen
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTourismUsabilityInformation systemValue (mathematics)Identity (music)Information accessPopulation

Abstract

fetched live from OpenAlex

The historical and cultural identity of Banyuwangi Regency needs to preserve its archaeological heritage. Assigning sites of historical value has, over the years, been left undertaken or ignored by the community at large. The advent of a Geographical Information System has provided an avenue for addressing these challenges through site documentation, preservation, and ease of access for navigation. In this scenario, the accuracy of archaeological data recording and ease of access are of paramount concern and are taken care of by the Banyuwangi Regency Tourism Office.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.005

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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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
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
Published2025
Admission routes1
Has abstractyes

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