Variability in micronekton active carbon transport estimates on the Southwest Coast of Oahu using three different sampling gears
Bibliographic record
Abstract
Micronekton were sampled off the southwest coast of Oahu in October of 2004 as part of the North Pacific Marine Sciences Organization (PICES) Micronekton Sampling Gear Intercalibration experiment (MIE-1). The initiative employed three different micronekton sampling gears: the Cobb Trawl, Isaacs–Kidd midwater trawl (IKMT), and Hokkaido University frame trawl (HUFT). Micronekton catches from the three sampling gears were used to quantify the rates of active carbon transport. We evaluate the differences in total active carbon transport assessed using the data collected by the three gears, with a particular emphasis on taxa- and length-specific differences across gears. The estimates of total active carbon transport derived from the HUFT were significantly lower than those derived from the IKMT. We detected no significant difference between estimates derived using the IKMT and Cobb and the Cobb and HUFT. Dominant groups contributing to active carbon transport varied across sampling gears (Cobb: myctophids and cephalopods; HUFT: decapods and stomatopods; IKMT: cephalopods, myctophids, and decapods); however, no significant differences in the contribution of individual taxa to active carbon transport across sampling gears were detected (e.g., the myctophid active carbon transport contribution for the Cobb was not significantly different from that of the IKMT). Pairwise ratios revealed size-specific differences in the contribution to total flux across gears. As expected, the HUFT and IKMT estimates of active carbon transport were higher for smaller size classes, while estimates from the Cobb were more evenly distributed across size classes. These findings suggest that the differences in total active carbon transport from the three sampling gears are driven primarily by size-based sampling biases, which produce significant differences in biomass estimates. This study provides a foundation upon which future active carbon transport studies may be adjusted to address sampling gear biases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".