Assembling a DNA barcode reference library for the spiders (Arachnida: Araneae) of Pakistan
Bibliographic record
Abstract
Morphological study of 1,795 spiders from sites across Pakistan placed these specimens in 27 families and 202 putative species. COI sequences >400 bp recovered from 1,782 specimens were analyzed using neighbor-joining trees, Bayesian inference, barcode gap, and Barcode Index Numbers (BINs). Specimens of 109 morphological species were assigned to 123 BINs with ten species showing BIN splits, while 93 interim species included representatives of 98 BINs. Maximum conspecific divergences ranged from 0-5.3% while congeneric distances varied from 2.8-23.2%. Excepting one species pair (Oxyopes azhari-Oxyopes oryzae), the maximum intraspecific distance was always less than the nearest-neighbor (NN) distance. Intraspecific divergence values were not significantly correlated with geographic distance. Most (75%) BINs detected in this study were new to science, while those shared with other nations mainly derived from India. The discovery of many new, potentially endemic species and the low level of BIN overlap with other nations highlight the importance of constructing regional DNA barcode reference libraries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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 | 0.001 |
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".