Otolith chemistry analyses indicate that water Sr:Ca is the primary factor influencing otolith Sr:Ca for freshwater and diadromous fish but not for marine fish
Bibliographic record
Abstract
Water chemistry is thought to be the primary factor influencing fish otolith chemistry. Experimental results with freshwater and diadromous fish have been consistent with this paradigm, but with marine fish, they have often been ambiguous or contradictory. A review of water chemistry data indicated that Sr:Ca (mmol:mol) levels were higher in marine water than in most freshwater systems and that Sr:Ca variability was lower in marine water than in most freshwater systems. We therefore hypothesized that lifetime otolith Sr:Ca profiles of freshwater fish would exhibit low levels of Sr:Ca with moderate variability, of diadromous fish would exhibit highly variable Sr:Ca levels, and of marine fish would exhibit high levels of Sr:Ca with low variability. Otolith Sr:Ca profiles from 81 species of freshwater, diadromous, and marine fish revealed that freshwater fish had low levels of Sr:Ca and lower variability than expected relative to marine fish, diadromous fish had Sr:Ca levels and variability that were consistent with expectations, and marine fish had high maximum Sr:Ca levels, as expected, and high Sr:Ca variability, similar in magnitude to diadromous fish, which was not expected. These findings indicate that water Sr:Ca is the primary factor influencing otolith Sr:Ca variation for freshwater and diadromous fish but not for marine fish.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".