Quantitative Classification and Ordination of the Forest Communities in Three Gorges Reservoir Area
Bibliographic record
Abstract
Forest plant communities in Three Gorges Reservoir Area were studied by the methods of two way indicators species analysis(TWSPAN)and detrended correspondence analysis(DCA).The results showed that forest plant communities were classified into 33 formations by TWSPAN,they were Form.Pinus henryi,Form.Pinus armandii,Form.Pinus massoniana,Form.Cunninghamia lanceolata,Form.Cupressus funebris,Form.Pinus massoniana-Quercus variabilis,Form.Pinus massoniana-Castanopsis fargesii,Form.Pinus massoniana-Grdonia axillaris,Form.Cunninghamia lanceolata-Castanopsis fargesii,Form.Quercus glandulifera var.brevipetiolata,Form.Quercus variabilis,Form.Quercus albus,Form.Quercus aliena-Quercus variabilis,Form.Quercus dentata var.oxyloba,Form.Fagus lucida,Form.Dendrobenthamia japonica var.chinensis,Form.Liquidambar formosana,Form.Castanea seguinii,Form.Platycarya strobilacea,Form.Betula albo-sinensis,Form.Betula utilis,Form.Cerasus conrodinae-Quercus spinosa,Form.Cercidiphyllum japonicum-Padus obtusata,Form.Bothrocaryum controversum,Form.Celtis sinensis,Form.Lithocarpus cleistocarpus-Castanea henryi,Form.P.strobilacea-Cyclobalanopsis oxyodon,Form.Lithocarpus glaber,Form.Castanopsis eyeri,Form.Ormosia henryi,Form.Machilus pingii,Form.\{G.asillaris\} and Form.Quercus spinosa.Results of ordination by DCA reflected basically the relationship between plant communities and environmental factors,axis 1 and axis 2 reflected mainly the thermal and moisture gradients respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".