Bibliographic record
Abstract
The forest vegetation of Mt. Seongju area, near Boryeong, was surveyed from August to October 2013. The vegetation of Mt. Seongju area classified into 13 main plant communities according to the dominant species: Pinus rigida community, Alnus hirsuta community, P. densiflora plantation, Larix leptolepis community, Chamaecyparis obtusa community, Pinus koraiensis community, Quercus variabilis community, Q. variabilis-P. densiflora community, Q. acutissima community, Q. mongolica community, P. densiflora community, P. densiflora - Q. variabilis community, and Carpinus laxiflora community. In addition, the Q. variabilis commintity is distributed on southern slope and Q. mongolica community on the northern slope. Carpinus laxiflora community distributed on the southern slope and ridge of the Mt. Seongju. Another specific communty was P. densiflora plantation, which was artificially planted as the purpose of a restoration after mining several years ago. Q. variabilis community showed higher diversity index than other communities. DGN 7 grade appeared 90.3% of Mt. Seongju area. The frequency distribution in DBH-class of dominant tree species for Q. mongolica community, P. densiflora community, and Carpinus laxiflora community showed stable community structure, but Quercus variabilis community showed intermediate stage of successional processes. The net primary productivity(NPP) was assumed as 1,588.22 g/m2/yr by Miami Model, and 1,488.39 g/m2/yr by Montreal model, respectively.
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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 | 0.001 | 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) | 0.002 | 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".