Second-order seasonal variability in diel vertical migration timing of euphausiids in a coastal inlet (supplemental data)
Bibliographic record
Abstract
************* VENUS ACOUSTIC DATA PACKAGE ************* VERSION 1.0. April 2016. DOI: 10.18357/SatoM.2016.data01 THE VENUS ACOUSTIC DATA PACKAGE ACCOMPANIES: Sato, M., J.F. Dower, E. Kunze, and R. Dewey. 2013. Second-order seasonal variability in diel vertical migration timing of euphausiids in a coastal inlet. Marine Ecology Progress Series 480: 39-56. doi: 10.3354/meps10215 It contains a copy of the processed acoustic data file exactly as used for this paper, as well as an example code (see below). Detailed analysis method was described in Sato et al. (2013). Original raw data are available through the Ocean Networks Canada. When you use this VENUS Acoustic Data Package, please cite Sato et al. (2013) in addition to this data sets. We also ask you to acknowledge the Ocean Networks Canada for collecting data and maintaining the cabled observatory. ********************** CONTENTS ********************** 1. README.txt - Including a description of the data and the literature source. 2. VENUS_Satoetal2013.mat - Volume backscattering strength (Sv in dB re 1 m^-1) data from 2008-Jun-01 through 2010-Jun-15 in UTC (1-min, 1-m averaged data), with corresponding time and depth variables. 3. plot_dvm.m - Example code to reproduce Fig. 2b in Sato et al. (2013).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.079 | 0.019 |
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".