ESTIMATION OF THE BIOMASS AND CARBON SEQUESTRATION POTENTIAL OF SELECTED PLANT SPECIES IN GARDENS OF PALANPUR
Bibliographic record
Abstract
The technique of extracting and storing carbon dioxide from the atmosphere is known as carbon sequestration. It is one way to lessen global climate change by lowering the atmosphere concentration of carbon dioxide. The two main forms of carbon sequestration that the USGS is evaluating are geologic and biologic. The research area of choice is Palanpur gardens which is located in Banaskantha, Gujarat, India. For the research I have selected three gardens in Palanpur which are Meena Bagh, District Garden and Shashivan. The study was conducted with quadrate random sampling method. There were 40 quadrates taken of 10x10 m2. In the research, 40 species, including 150 individuals have been recorded in Palanpur gardens. The field data of the trees analyzed using the random sampling of quadrate method, which shows the dominant tree species in each quadrate is Azardirachta indica as total of 16 tree species in 13 quadrates. While the dominant species found in 40 quadrates which are Acacia catechu, Acacia nilotica, Aegle marmelos (L) corr, Albizia labbeck, Annona squamosa, Bombax ceiba, Caryota urens, Cassia fistula, Cordia diacotoma G. Forst, Delonix regia, Ficus recemosa, Ficus religiosa, Hyophorbe langenicaulis, Nyctanthus arbortristis Linn, Pithecellobium dulce, Polyalthia longifolia and Syzygium cumini with the total number of species 4, 4, 4, 4, 6, 5, 4, 4, 4, 6, 6, 6, 7, 4, 4, 15, 4 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 | 0.001 |
| 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 | 0.000 |
| 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".