The Study on Flow Velocity Measurement of Antarctic Krill Trawl Model Experiment in North Bay of South China Sea
Bibliographic record
Abstract
From August 25 to 29, 2014, the project team carried out the experiment of Antarctic krill trawl in the Beihai Bay of the South China Sea. In order to understand the flow field of the network model in the course of the experiment, it is necessary to record the speed of the ship and to grasp the flow field of the ocean. Therefore, the ocean velocity is measured during the experiment. The flow rate in this experiment was measured using an acoustic Doppler flow meter (Vectoring Plus, Nortek, Norway). In order to compensate for the flow rate error caused by ship drift, the drift condition of the ship was also measured by the positioning device (Snapdragon MSM8274AB, Qualcomm, USA) used in the flow rate measurement. The results show that the actual velocity of the target sea area is in the range of 0.06-0.49 m / s and the direction is 216.17-351.70. And compared with the previous research, the influencing factors were analysed. This study proves that it is feasible to use point Doppler flow meter for velocity study in trawl model experiment.
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 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 | 0.001 | 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) | 0.000 | 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".