Passive acoustic monitoring data recorded by recorder ICL1212 at mooring DBS08-04 in the German Bight, North Sea, in 2017
Bibliographic record
Abstract
Passive acoustic monitoring (PAM) data were collected by recorder ICL1212 of type icListen (manufactured by Ocean Sonics, Truro, Canada) at 54.5742° N, 6.1125° E, mooring DBS08-04, in the German Bight, North Sea. Passive acoustic data were collected from March 2017 to April 2017 by IC1212. The recorder was moored at 39 m depth and scheduled to record at a duty cycle of 10 min per 30 min and at a sample rate of 4,000 Hz. Further details about the data acquisition and processing of this data set can be found in the accompanying metadata file (see Additional metadata) as well as the data processing report (see Data Processing Report). Passive acoustic data archived here represent data processing Level 1+, according to the standards defined in the associated Standard Operation Procedure (SOP) Glossary (Thomisch et al. 2023a). Further information on data processing with regard to data preparation and standardization can be found in the associated SOP Part 1: Data preparation and standardization (Thomisch et al. 2023b).
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.018 |
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".