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Heavy Metals in Surface Sediments of the Coastal Area Around Daerah Istimewa Yogyakarta, Indonesia: Their Relations to Land-Use Types

2023· article· en· W4379053080 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIraqi Geological Journal · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Pollution Remediation
Canadian institutionsnot available
FundersDirektorat Riset dan Pengabdian MasyarakatUniversitas Gadjah MadaBadan Riset dan Inovasi Nasional
KeywordsAgricultural landSedimentMangroveEnvironmental sciencePollutionLand useUrbanizationCadmiumHeavy metalsContaminationEnvironmental protectionGeographyHydrology (agriculture)EcologyEnvironmental chemistryGeology

Abstract

fetched live from OpenAlex

The province of Daerah Istimewa Yogyakarta (DIY) has experienced significant changes in urbanization, industry, and tourism, making it one of Indonesia's fastest-growing areas. Increased anthropogenic activity in the coastal region may cause heavy metal contamination in that zone to grow. Based on different land-use types, this study examined the distribution of heavy metals, namely cadmium (Cd), lead (Pb), copper (Cu), and zinc (Zn), in surface sediment. It assessed the feasibility of sediment quality standards based on the Canadian Sediment Quality Guidelines (CSQG). Nine stations made up the sampling site, each representing a different land-use type, including mangrove ecosystem, tourist attraction, airport, harbor, mining area, bare land, shrimp pond, agricultural land, and settlement. The concentrations of Cd in bare land, shrimp pond, agricultural land, and settlement (with values of 2.707, 2.955, 2.983, and 2.873, respectively), and Cu in the mangrove ecosystem (with values of 42.893) slightly exceeded the corresponding Threshold Effect Level (TEL) value of CSQG. Meanwhile, the content of other heavy metals in all land use types tends to be low, even below the Limit of Detection (LOD). The data on the level of heavy metal pollution in the study area shows no connection between heavy metal contamination and different land-use types. It is brought on by a variety of circumstances, such as the fact that human activity in the study area did not significantly contribute to heavy metal contamination or that heavy metals were contaminated and then spread to other forms of land-use types, in this case, the mangrove ecosystem, by runoff and wind. This is because variations in salinity, estuary flushing, physical mixing and dilution, and chemical processes, including sorption, complexation, cation exchange, and redox reactions, all affect how heavy metals are transported by water. The government should create environmental regulations, laws, quality norms and standards, more funding for cutting-edge scientific research, and technical tools to prevent heavy metal pollution in coastal areas.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.040
GPT teacher head0.264
Teacher spread0.224 · 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