Eastern Arctic and Subarctic Sponge Identification - DFO Multispecies Trawl Surveys (2010-2014, 2017 and 2019)
Bibliographic record
Abstract
Sponges (phylum Porifera) are benthic filter feeding animals that play an important role in nutrient cycling and habitat provision in the deep sea. However, despite these key functional roles, sponge communities in Arctic marine environments are still poorly known. Sponges were collected between 2010-2014, in 2017 and in 2019 during annual multispecies trawl surveys conducted by Fisheries and Oceans Canada in Baffin Bay, Davis Strait and portions of Hudson Strait. They were taxonomically examined under a microscope and it resulted in a dataset of approximately 2700 sponge specimens identified, comprising ~100 known sponge taxa. Sponges from various poescilosclerid families are described in this technical report series. For each species presented in these reports, a physical description, a discussion of their distinguishing characteristics, the dimensions and descriptions of their spicules, photos of the sponge and spicules, a map of the sampling locations, and taxonomic remarks are included. The present data package includes links to all these arctic sponge technical reports alongside the datasets of all specimens supporting the taxonomic description process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.016 |
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".