Electronic archival tags provide first glimpse of bathythermal habitat use by free-ranging adult lake sturgeon<i>Acipenser fulvescens</i>
Bibliographic record
Abstract
Information on lake sturgeon (Acipenser fulvescens) depth and thermal habitat use during non-spawning periods is unavailable due to the difficulty of observing lake sturgeon away from shallow water spawning sites. In 2002 and 2003, lake sturgeon captured in commercial trap nets near Sarnia, Ontario were implanted with archival tags and released back into southern Lake Huron. Five of the 40 tagged individuals were recaptured and were at large for 32, 57, 286, 301, and 880 days. Temperatures and depths recorded by archival tags ranged from 0 to 23.5 ºC and 0.1 to 42.4 m, respectively. For the three lake sturgeon that were at large for over 200 days, temperatures occupied emulated seasonal fluctuations. Two of these fish occupied deeper waters during winter than summer while the other occupied similar depths during non-spawning periods. This study provides important insight into depth and thermal habitat use of lake sturgeon throughout the calendar year along with exploring the feasibility of using archival tags to obtain important physical habitat attributes during non-spawning periods.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".