Bibliographic record
Abstract
Based on the planktons sampled in the Jiaozhou Bay during the time period from January to De-cember 2003,totally 71species of zooplankton and 34groups of plankton larvae are identified.The spatial-temporal distribution and variation of the species,and their relationships to the environmental factors of the sea area are analyzed.As it is shown by the results from the analysis and the comparison with the his-torical data,the zooplankton species diversity is in accordance with the general rule of the zooplankton dis-tribution in the mid-latitude bay waters.The ecological attributes is mainly of the in-shore and low-salt species of the warm temperate zone.Zooplankton biomass and abundance vary from season to season.The annual mean biomass is 84.28mg/m3,the mean nutrimental zooplankton abundance is 531.76ind/m3,and the counterpart of non-nutrimental zooplankton 72.08ind/m3.The seasonal variation of the zooplankton biomass and the nutrimental zoolankton abundance accords with that of the water temperature.It is evi-denced from the regression analysis for the correlative factors that they can be more closely related to the temperature variation.The temporal-spatial distribution of zooplankton and the species diversity do not va-ry much and maintain a similar variation in the recent 20years.Although there is temporal difference a-mong the annual peak times of the biomass and abundance,it can be attributed to the temperature abnor-mality in the inter-annual variation and the seasonal variation.
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 | 0.000 | 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".