Analysis of Reduce Potential Methane Gas Emission by Methanotrofic Bacteria from Rice Field in Gowa
Bibliographic record
Abstract
The Increase of temperature in atmosphere caused by increasing concentrations of methane in rice field affects to metabolism of rice plants, it can reduce productivity of rice. Methanotrofic bacteria are one of the organisms that can reduce methane gas emissions, because the bacteria use methane as an energy source. Based on the fact, needed information about the reduce potential of methane gas by the bacteria. The aim of this study was to analyze reduce potential of methanotrofic bacteria have been previously isolated that from rice fields in Gowa. The Analysis was done by measuring concentration of methane gas using chromatography gas techniques. Observations of remaining gas concentration were done four times during 13-days incubation period. All isolates were able to reduce methane with varies potential. The highest reduction shown by isolates GMP 2 with the reduction about 88%. The Lowest reduction shown by GMV 3 with the reduction about 51.9%. Keywords: emission, methane, methanotrofic
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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) | 0.001 | 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 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".