MétaCan
Menu
Back to cohort
Record W4381621844 · doi:10.31315/psb.v4i1.8828

Karakteristik Air dan Perkiraan Suhu Reservoir Panas Bumi di Desa Kalibeber, Kecamatan Mojotengah, Kabupaten Wonosobo, Provinsi Jawa Tengah

2023· article· id· W4381621844 on OpenAlexaff
Veronika Cendi Prameswari Putri, Agus Bambang Irawan, Andi Renata Ade Yudono

Bibliographic record

VenueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMI · 2023
Typearticle
Languageid
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsEnvironmental scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Desa Kalibeber merupakan salah satu desa di Kabupaten Wonosobo yang memiliki manifestasi panas bumiberupa mata air panas. Interaksi yang terjadi antara batuan dengan larutan hidrotermal dapat mengakibatkanterubahnya mineral yang dapat mempengaruhi karakteristik mata air panas. Penelitian ini bertujuan untukmengetahui karakteristik dan suhu bawah permukaan air panas bumi di daerah penelitian. Metode yangdigunakan adalah survei dan pemetaan, uji laboratorium dan analisis geokimia air. Hasil penelitian menunjukkanbahwa mata air panas memiliki karakteristik yaitu termasuk tipe mata air tahunan, debit kelas V, mata air panasdengan suhu 39oC, tipe air bikarbonat serta batuan pada lokasi penelitian belum mengalami alterasi. Potensimata air berdasarkan kualitas mata air secara fisik yaitu, tidak berbau, tidak berasa dan berwarna kuning. Suhubawah permukaan sekitar 172oC yang termasuk entalpi sedang sehingga fluida panas bumi hanya dapatdigunakan secara langsung.Kata Kunci: Panas Bumi, Mata Air Panas; Karakteristik; Suhu; Geokimia

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.241
Teacher spread0.207 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMISame topicGeological and Geophysical StudiesFrench-language works237,207