Resource Use of Rodent Community in the Sandland of Erdos Plateau III── Analysis of Using Pattern for Time
Bibliographic record
Abstract
In Kubuqi sandland of Erdos plateau, from 1991 to 1996, we collected the datum of 42 months about three-toed jerboa (Dipus sagitta),dersert hamster (Phodopus roborovskii), Chinese jird (Meriones meridianus), striped hamster (Cricetulus barabensis),five-toed jerboa (Allactaga sibirica), and ground squirrel (Citellus dauricus), and we focused to describe their seasonality, inter annual change and trends by moving average and analysis of PCA. The results show: First, their population dynamics are all single peak in one year, and for every month except June, one of six species will have the highest peak of its number at this year. The seasonable dynamics for six population is different, three-toed jerboa has the most remarkable seasonal change, five-toed jerboa, desert hamster, Chinese jird and striped hamster have a decline successively, and the last is ground squirrel. Second, for inter annual dynamics, the change three-toed jerboa and five-toed jerboa are more stable, Chinese jird and desert hamster are the same as parabola, striped hamster and ground squirrel have a marked ascendant. By comparison with seasonal dynamics, the inter annual fluctuation of six species is not obvious. Third, six species have a remarkable descending or ascending trends. The last, we analyzed the using pattern of rodent community for time.
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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 | 0.000 |
| 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".