MétaCan
Menu
Back to cohort
Record W2986602855 · doi:10.33021/jmem.v4i2.827

Identifikasi Genangan Banjir yang Terjadi di Kecamatan Cikampek, Kabupaten Karawang

2019· article· en· W2986602855 on OpenAlexaff
Deandra Auliana Izmah, Eka Wardhani, M. Candra Nugraha

Bibliographic record

VenueJournal of Mechanical Engineering and Mechatronics · 2019
Typearticle
Languageen
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsWiLAN (Canada)Encana (Canada)
Fundersnot available
KeywordsHydrology (agriculture)DrainageGeographyHuman settlementFlood mythAllotmentWater resource managementEnvironmental scienceGeologyArchaeologyEcology

Abstract

fetched live from OpenAlex

Cikampek District is one of the sub-districts in the Karawang Regency located in the Southeast part of the Karawang Regency area. Cikampek sub-district is one of the areas that is growing rapidly due to the development of industrial allotment areas and urban settlements. This study aims to determine the flood inundation that must be addressed immediately. The research method was carried out by observation in the field and interviews with related parties. Based on the results of research in the District of Cikampek, there was inundation with an area of 274 Ha, inundation height of 10-40 cm, drainage time of 3 hours / day, and inundation frequency (9 times / year) due to overflow of secondary drainage channel namely Cikaranggelam River. There are three priority areas that the drainage system must immediately address, namely Desa Cikampek Selatan, Dawuan Tengah and Dawuan Barat.

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)0.001
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 score0.011
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Mechanical Engineering and MechatronicsSame topicMultimedia Learning SystemsFrench-language works237,207