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Record W3010621598 · doi:10.12962/j2716179x.v11i1.5212

Technology Foresight Analysis Sebagai Metodologi Dalam Pertimbangan Pengembangan Kawasan Cagar Budaya

2016· article· ms· W3010621598 on OpenAlex
Karina Pradinie, Rimadewi Suprihardjo, Dian Rahmawati, Rulli Pratiwi Setiawan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Penataan Ruang · 2016
Typearticle
Languagems
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Management
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesFutures studiesPhilosophyComputer science

Abstract

fetched live from OpenAlex

Metodologi dalam penelitian kawasan cagar budaya sangat potensial untuk dikembangkan, terutama dalam pendekatan-pendekatan non fisik seperti partisipasi masyarakat. Aspek anthropologi yang dipotret dengan bingkai kajian etnografi, aspek ekonomi dan lingkungan aspek modal budaya dan berlanjutan. Dalam pengembangan cagar budaya, sangat diperlukan aspek-aspek yang akan mendukung masa depan cagar budaya. Pengetahuan terhadap aspek-aspek tersebut yang dibingkai dalam analisis foresight yang dikembangkan diharapkan bisa menjadi pertimbangan dirumuskan kebijakan-kebijakan yang dapat mendukung pengembangan kawasan cagar budaya ke depan. Keywords : Foresight Analysis, Cagar Budaya , Pengembangan Metode

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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