Analysis of Suitable Habitat for Nesting of Hawksbill Turtles (Eretmochelys imbricata) in Pulau Sangiang Natural Park, Banten
Bibliographic record
Abstract
The Sangiang Island Nature Tourism Park (TWA Pulau Sangiang) is a small island in the Sunda Strait that serves as a nesting habitat for hawksbill turtles (Eretmochelys imbricata). This study aims to analyze the suitability of beaches in TWA Pulau Sangiang as a nesting site. The research employs a qualitative method with direct field observation techniques, interviews, and documentation. The data measured include beach slope, beach width, nest temperature, nest humidity, beach sand pH, sand substrate, beach vegetation, natural predators, and human disturbances. The data were analyzed descriptively using a habitat suitability index for turtle nesting. The measurements show that Villa Bubu Beach has a beach width of 6.4 meters with an average slope of 10º. The sand substrate on this beach is dominated by 97.38% medium sand. Nest temperatures on this beach are 28℃ with dry humidity and an average pH ranging from 6.5 to 7. Meanwhile, Sepanjang Beach has an average beach width of 27.15 meters with a slope ranging from 9.1º. The sand substrate is dominated by 99.47% medium sand. Nest temperatures on this beach average 30℃ with dry humidity and a pH of 6.5–7. The coastal vegetation at Villa Bubu Beach is dominated by Casuarina trees (Casuarina equsetifolia), while the vegetation at Sepanjang Beach is dominated by Sea Lettuce Trees (Scaevola taccada) and Screw Pines (Pandanus tectorius). Natural predators on both beaches include monitor lizards and wild boars. Based on these measurements, Villa Bubu Beach and Sepanjang Beach in TWA Pulau Sangiang are highly suitable as nesting habitats for hawksbill turtles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".