Bibliographic record
Abstract
In order to make out the effective program on the tourist source of tourism market in Ningxia,the paper,concentrating on the development of tourist sources,thoroughly and carefully divides the markets of foreign and domestic tourist sources of Ningxia Markov Prediction Methods and Tourism Attenuation Theory.Three-level markets are found according to objective foreign tourist sources: the first-level market is France,Germany and America;the second-level market is Japan,Canada,Italy,New Zealand and Russia;and the third-level market is UK and Australia.As for domestic tourist sources,Ningxia itself is marked as the first-level market,Inner-Mongolia,Gansu Province and Shanxi Province as the second level market and other provinces as the third one.According to the above division,the paper suggests the idea of shaping the superior tourism brand with its own features,which offers the theoretical warranty to the systematical programming on market of tourist sources as well as favorable development of featured tourism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".