www.mapress.com/zootaxa / Correspondence
Bibliographic record
Abstract
Ecuador is considered one of the most biodiverse countries in the world (Mittermeier et al. 1997), yet its spider fauna is unknown and understudied. Only 709 species distributed in 43 families are known to occur in Ecuador (Platnick 2013), whereas in Canada, a country much less biodiverse, the spider fauna is composed of 1405 spider species distributed in 43 families (Paquin et al. 2010). It seems reasonable to assume that a large part of the Ecuadorian spider fauna is still undiscovered. Furthermore, some groups are badly in need of revision, many species are known only from the type specimens, old descriptions and in some cases no illustrations were provided by the author making it difficult to recognise these species. In 1909, Embrik Strand described 17 new species of Ctenus Walckenaer, 1805 from South America (Strand 1909); seven of these species (three from Ecuador and four from Brazil) have never been illustrated or included in any recent taxonomic work. Even though Strand’s descriptions are quite elaborate, he did not provide any illustrations, thus making the identification of his species difficult. This paper is the first of two papers on Embrik Strand’s mysterious Ctenus species. The first part includes redescriptions and illustrations for the first time of the three
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.947 | 0.909 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".