DNA barcoding of spiders from agricultural fields
Bibliographic record
Abstract
In the present study, DNA barcoding was used to assess the percentage accuracy of morphological base identification of spiders from the agriculture fields of district Layyah, Punjab, Pakistan. A total of 872 spiders were captured from June to August of 2017. All the collected spiders were brought to molecular laboratory at GC University Lahore, preserved in 95% ethanol and stored at -20 °C until the DNA extraction. Spiders were evaluated morphologically on the basis of different identification Keys and Catalogs. Morphological identification revealed the presence of 12 families, 29 genra and 49 species. To evaluate the authenticity of morphological identification, tissue samples of 96 specimens were sent to Canadian Center for Biodiversity and Genomics, University of Guelph, Canada. A 658-base pair sequence of COI (Cytochrome c Oxidase Subunit I) of 90 specimens was retrieved successfully, which confirmed the presence of 11 families, 25 genra and 47 species. On the basis of molecular results, all the misidentified specimens were then allotted the correct taxon. Overall accuracy of morphological based identification was 88%. It is concluded from the present study that morphological investigations to identify a spider, are satisfactory but to enhance the accuracy, pace and credibility of results, molecular technique like DNA barcoding is considerable. Furthermore, to magnify authenticity of evaluation of spiders, integrated barcoding- combination of molecular methods and conventional taxonomy- is compulsory.
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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 | 0.000 |
| 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".