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Record W1513655537 · doi:10.17146/gnd.2003.6.2.205

IDENTIFIKASI RADIONUKLIDA PEMANCAR GAMMA DI DAERAH PANTAI LEMAHABANG MURIA DENGAN SPEKTROMETRI GAMMA

2003· article· id· W1513655537 on OpenAlexaff
Sukirno Sukirno, Agus Taftazani

Bibliographic record

VenueGANENDRA Majalah IPTEK Nuklir · 2003
Typearticle
Languageid
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

lDENTIFIKASl RADIONUKLlDA PEMANCAR GAMMA DI DAERAH PANTAI LEMAHABANG MURIA DENGAN SPEKTROMETRI GAMMA. Rencana lokasi terpilih Pusat Listrik Tenaga Nuklir (PLTN) yang akan dibangun terletak di sekitar pantai Lemahabang semenanjung Muria Jawa Tengah. Dalam rangka antisipasi kemungkinan terjadi perubahan radioaktivitas karena pembangunan PLTN, perlu dipersiapkan data awal konsentrasi radioaktiviras alami di daerah tersebut. Tujuan utama identifikasi ini dilakukan untuk mengetahui radioaktivitas gamma serta radionuklida lingkungan yang terdapat dalam cuplikan algae, ikan kerapu, sedimen dan air laut. Pengambilan cuplikan, preparasi maupun analisisnya mengacu pada prosedur analisis cuplikan radioaktivitas lingkungan. Instrumen yang digunakan adalah Maestro II EG&G spektrometer γ Ortec dengan detektor Ge(Li). Hasil identifikasi radionuklida alam pemancar γ dengan teknik spektrometri γ menunjukkan ada 6 jenis radionuklida alam yang teridentifikasi yaitu Ra-226 (186,52 keV), Pb-212 (238,75 keV), Pb-214 (395.94 keV), Tl-208 (583,19 keV), Ac-288 (911,07 keV) dan K-40 (1460,7 keV). Radioaktivitas γ untuk semua radionuklida dalam air laut masih jauh di bawah nilai batas radioaktif lingkungan menurut SK DIRJEN BATAN No 294/DJ/1992. Radioaktifitas pemancar γ tertinggi dalam air laut adalah K-40 terukur dengan konsentrasi 5,798 ± 0,537 Bq/L, sedangkan konsentrasi tertinggi yang diijinkan 104 Bq/L.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.026

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 head0.019
GPT teacher head0.210
Teacher spread0.191 · 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; both teacher heads agree on what is shown here.

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
Published2003
Admission routes1
Has abstractyes

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