Genetic Diversity of Philodromus cespitum (Walckenaer, 1802) (Philodromidae); An Effective Biocontrol Agent
Bibliographic record
Abstract
Abstract In this study, mtCOI data of Philodromus cespitum (Walckenaer, 1802) (Philodromidae) collected from Türkiye and mtCOI data obtained from other countries such as Canada, Spain, Norway, the Netherlands, the United States of America, Germany, Finland and Bulgaria were combined and analysed to determine the genetic diversity of P. cespitum. 360 sequence data sets were evaluated, resulting in the identification of 155 haplotypes. The nucleotide frequencies were given in percent; T: 41.15; C: 12.88; A: 29.38 and G: 16.58 and revealed that the base compounds were directed towards Thymine–Adenine (70.53%). Analyses of sequence variation in a 781 bp of (cox1) gene revealed low nucleotide diversity (Pi: 0.016) but high haplotype diversity within populations (Hd = 0.971). According to the neutrality test (Tajima’s D and Fu’s Fs), the populations showed a strong spread (p < 0.05). P. cespitum was polyphage and dominant in agricultural areas. The specimens had spread in different habitat characteristics and different geographic regions. The species had wide tolerance in term of environmental differences. The genetic diversity of the species did not change much, even under different ecological conditions and geographical regions. As a result, the low genetic diversity of P. cespitum provides a selective advantage in biological control.
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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 | 0.000 | 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) | 0.001 | 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".