Systematic revision of the family Tetillidae (Porifera: Demospongiae) in the temperate Northeast Pacific
Bibliographic record
Abstract
Abstract This study presents the first comprehensive systematic revision of the sponge family Tetillidae in the temperate north-east Pacific. The findings reveal a previously unrecognized clade of Tetilla species that inform the family’s generic classification, including a common California species whose identity has long been uncertain. Remarkably, eight species were discovered from only 11 samples from the Aleutian Islands of Alaska, suggesting that these islands harbour considerable undiscovered sponge diversity. I also report the first likely case of species’ introduction in the family: an Asian species, probably Tetilla japonica, appears to have been introduced to Southern California. In total, this work refines our understanding of nine previously described species and formally describes eight new species as Craniella amlia sp. nov., Craniella shemya sp. nov., Craniella columbiana sp. nov., Craniella rocheta sp. nov., Craniella uniiguni sp. nov., Craniella vermisigma sp. nov., Tetilla losangelensis sp. nov., and Tetilla vancouverensis sp. nov.. Multi-locus DNA sequence data are presented for 13 species, including several low-coverage mitochondrial genomes and complete ribosomal sequences assembled de novo from Illumina sequencing. Together, these results significantly advance our understanding of global tetillid diversity, systematics, and the biogeography of sponge diversity in the north-east Pacific.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".