Virkninger av forurensning på biologisk mangfold: Vann og vassdrag i by - og tettstednære områder. Fastsittende alger i rennende vann - en kunnskapsstatus
Bibliographic record
Abstract
Det gis en kunnskapsstatus for mangfold av fastsittende alger i rennende vann i Norge. Det fokuseres på variasjoner i mangfold langs naturgitte og menneskeskapte gradienter. Artsmangfoldet er stort, de mest artsrike gruppene er cyanobakterier, grønnalger og kiselalger. Mange har tydelige geografiske tyngdepunkt i Norge og ikke alle ser ut til å være kosmopolitter. Mangfoldet per stasjon dobles fra vår til sommer/høst. Brukes artsantall på den enkelte lokalitet som kriterium bidrar særlig fosfor og tungmetaller til redusert mangfold. Langs en gradient av fosfor er mangfoldet maksimalt ved 3-7 µg totP/L, over 20 µg totP/L er mangfoldet halvert. At det ikke er dokumentert noe generelt avtak i mangfoldet langs gradienter av pH og totN skyldes trolig at næringsstoffene karbon og nitrogen opptrer i ulike tilstandsformer langs disse gradientene. Det er forøvrig dokumentert markerte artsutskiftninger langs gradienter av kalsium, pH, totP og totN. Det er ikke dokumentert direkte tap av fastsittende alger i Norge, men flere forhold tilsier at dette er sannsynlig.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.011 |
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".