Comparing productionbiomass ratios of benthos and suprabenthos in macrofaunal marine crustaceans
Bibliographic record
Abstract
Using available data from the literature, we compared the productionbiomass ratios (P/B) between the suprabenthic (= hyperbenthic) and the benthic (infaunaepifauna) species within the group of the macrofaunal marine crustaceans. This data set consists of 91 P/B estimates (26 for suprabenthos and 65 for infaunaepifauna) for 49 different species. Suprabenthic crustacean P/B was significantly higher than P/B of benthic crustacean (post-hoc Scheffé test; one-way analysis of covariance, ANCOVA; p < 103) and also of other (noncrustacean) benthic invertebrate (p < 104). Predictive multilinear regression (MLR) analysis for macrofaunal marine crustaceans showed P/B to depend significantly on mean annual temperature (T) and mean individual weight (W) (R2 = 0.367). Adding the variable swimming capacity increased goodness-of-fit to R2 = 0.528. The higher P/B of suprabenthic (= swimming) macrofauna in comparison with that of the benthic compartment seems to be related to the most apparent feature of the suprabenthos, its swimming capacity. The high P/Bs reported for suprabenthic species indicate how a nontrivial part of benthic production can be ignored if suprabenthos is not well sampled, therefore biasing the models of energy flow generated for trophic webs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".