Investigating the effects of mobile bottom fishing on benthic carbon processing and storage: a systematic review protocol
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Marine sediments represent one of the planet’s largest carbon stores. Bottom trawl fisheries constitute the most widespread physical disturbance to seabed habitats, which exert a large influence over the oceanic carbon dioxide (CO 2 ) sink. Recent research has sparked concern that seabed disturbance from trawling can therefore turn marine sediments into a large source of CO 2 , but the calculations involved carry a high degree of uncertainty. This is primarily due to a lack of quantitative understanding of how trawling mixes and resuspends sediments, how it alters bioturbation, bioirrigation, and oxygenation rates, and how these processes translate into carbon fluxes into or out of sediments. Methods The primary question addressed by this review protocol is: how does mobile bottom fishing affect benthic carbon processing and storage? This question will be split into the following secondary questions: what is the effect of mobile bottom fishing on: (i) the amount and type of carbon found in benthic sediments; (ii) the magnitude and direction of benthic-pelagic carbon fluxes; (iii) the biogeochemical, biological, and physical parameters that control the fate of benthic carbon; and (iv) the biogeochemical, biological, and physical parameters that control the fate of resuspended carbon. Literature searches will be conducted in Web of Science, SCOPUS, PROQUEST, and a range of grey and specialist sources. An initial scoping search in Web of Science informed the final search string, which has been formulated according to Population Intervention Comparator Outcome (PICO) principles. Eligible studies must contain data concerning a change in a population of interest caused by mobile bottom fishing. Eligible study designs are Before and After, Control and Impact, and Gradient studies. Studies included at full-text screening will be critically appraised, and study findings will be extracted.Extracted data will be stored in an Excel spreadsheet. Results will be reported in narrative and quantitative syntheses using a variety of visual tools including forest plots. Meta-analysis will be conducted where sufficient data exists.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it