Waarnemingen van de mosdiertjes <i>Cryptosula pallasiana</i> (Moll, 1803), <i>Bugula stolonifera</i> Ryland, 1960 en <i>Bugula neritina</i> (Linnaeus, 1758) nieuw voor de Belgische fauna
Bibliographic record
Abstract
During surveys in the harbour of Oostende three bryozoan species new for the Belgian fauna were found. Cryptosula pallasjana (Moll, 1803) is a common fouling species on ships hulls and other floating objects in the Mercator yachting harbour in Oostende. EIsewhere along the Belgian coast this conspicuous species has not yet been encountered. Bugula stolonifera Ryland, 1960 is abundant in the harbour docks of Oostende where it occurs on ships hulls, floating objects and on all sorts of harbour constructions that remain permanently submerged. The species, which was also present in the harbour of Zeebrugge has shown a remarkable phenomenon. During the summer, some colonies get released from their substrate forming rather spherical, free living colonies. Both species, although only recently discovered, must have beer introduced some years or some decades earlier. The southern species Bugula neritina (Linnaeus, 1758) proved to be very common on a ship's hull at the end of March 1999. The yacht had not sailed very much and certainly not visited southern harbours This was the first occurrence of B. neritina in the Southern North Sea and so far the only one. This species has, contrary to the two former species, not yet established itself along the Belgian coast.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".