Monitoring Indo‐Pacific humpback dolphin occurrences in a highly urbanized estuary for informing conservation and management
Bibliographic record
Abstract
Abstract The estuaries within the Pearl River Delta are sites for large‐scale urban development and offshore construction. These projects have conservation stakeholders calling for more protection for the Indo‐Pacific humpback dolphins whose habitat overlaps with current and proposed construction sites. Efforts to improve impact assessments are hindered by the lack of baseline data and comprehensive understanding of how often the dolphins are present in areas near or within locations targeted for further development. The Modaomen Estuary within the Pearl River Delta is a good example of this, with little consideration for the dolphins as no data on their diurnal and seasonal occurrences within the estuary exist. A passive acoustic monitoring system was deployed over a calendar year from October 2016 to September 2017 to monitor the presence of humpback dolphins in the Modaomen Estuary. Results indicated that the estuary is an important area for humpback dolphins, with regular diel rhythms and seasonality in detection rates. For example, higher detections were seen during the wet season than during the dry season. However, there was no significant difference in detection rates between the flood and ebb tides, or between high and low tidal phases. Since the Modaomen Estuary is targeted for further development in the near future, these data provide the rationale for resource management and consent processes to consider potential impacts on the dolphins, as well as to aid marine spatial planning and conservation measures.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".