Molecular study to the fungus Neosetophomasamarorum was isolated from Al Chabaish marsh, South of Iraq دراسة جزيئية للفطر Neosetophomasamarorum المعزول من هور الجبايش جنوب العراق
Bibliographic record
Abstract
Neosetophomasamarorumis one of the phoma fungi put up with Ascomycota isolated from sea phoma. In this study,N. samarorumwas isolated fromAl Chabaish marsh, south of Iraq.This research aimed to the fungus Neosetophomasamarorum's molecular characterization using ITS gene and phylogenetic structuring tree.From35 samples of water collected from a different marsh area, eight samples were positive to Neosetophomasamarorum when cultured on PDA medium at 28C°, and 27samples were negative fungus. Genetic diagnosisresults for the fungus used specific primers for the ITS gene; thisdesign, especially for this project,showed that 8 (22.8%) were positive. The fungus was diagnosis depending onthe cultural feature and microscopic examination, and then PCR technology was used to ensurethe diagnosis of this fungus. Primers (ITS) and phylogenetic structuring treeanalysis were done by sequences and confirmation ofmicroorganism’s homogenous data using the database (NCBI) after amplifying Fungi’s ribosomal RNA. The resultshowed the genetic affinity percentage of N. samarorum between Germany and Canada is 99%, then among Poland, Canada and Germany are 99%, while between Netherland and Netherland is 96%, between Iran and China is 98%, and between Iran and China and Netherland are 96%.
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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) | 0.001 | 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".