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Record W4409173277 · doi:10.1051/bioconf/202517102014

The relationship between phytoplankton community structure and water conditions at Margagiri-Grenyang coastal waters, Banten Bay

2025· article· en· W4409173277 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.

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

Bibliographic record

VenueBIO Web of Conferences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBayPhytoplanktonEnvironmental scienceOceanographyCommunity structureHydrology (agriculture)GeologyEcologyBiologyGeotechnical engineeringNutrient

Abstract

fetched live from OpenAlex

Margagiri-Grenyang coastal waters are shallow water with substrate generally in the form of sandy mud that is busy with various activities, i.e. fishing, transportation, beach development for settlements, and industry. This can disrupt the stability of water conditions and the structure of the organism community in the bay. This study aimed to analyze the structure of phytoplankton communities, including the composition and abundance of types, diversity, evenness, and dominance indices, as well as their relationship with the water quality in these areas. This study was conducted for five months (July–November 2022) at six stations. The study showed that phytoplankton in these waters consisted of six classes and was dominated by the class Bacillariophyceae. Chaetocheros sp. and Thallasionema sp. were the genera commonly found in the waters. The values of the phytoplankton diversity, evenness, and dominance indices were 1.2733–2.5515, 0.3849–0.8003, and 0.1106-0.4912, respectively. Bacillariophyceae, Euglenophyceae,and Chrysophyceae appeared to be correlated with phosphate and total suspended solids (TSS).

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)0.000
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 score0.048
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.239
Teacher spread0.219 · 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