<i>In vitro</i> effects of increased temperature and decreased <scp>pH</scp> on blood oxygen affinity of 10 fish species of the <scp>A</scp>mazon
Bibliographic record
Abstract
Blood-O2 affinities (P50 ) were measured over a physiologically relevant pH range at 31 (highest temperature average of Rio Negro over the last 8 years), 33 and 35° C for 10 species of the Rio Negro, aiming to test the acute effects of temperature foreseen by the IPCC (Intergovernmental Panel on Climate Change) for coming years. The animals were collected during an expedition to the Anavilhanas Islands of the Rio Negro, 110 km upstream from Manaus (2° 23' 41″ S; 60° 55' 14″ W). Hoplias malabaricus showed higher blood-O2 sensitivity to pH changes (Bohr effect, Φ = Δlog10 P50 ΔpH(-1) ) at both 31° C (Φ = -0·44) and 35° C (Φ = -0·26) compared to Osteoglossum bicirrhosum (Φ = -0·54 at 31° C and Φ = -0·58 at 35° C), but lower P50 under most conditions, and a greater sensitivity of P50 to temperature. Two out of the 10 analysed species had significant increases of P50 (lower blood-O2 affinity) at the highest temperature throughout the pH range tested. For all other species, a minor increase of P50 over the assay-tested temperatures was observed, although all presented a normal Bohr effect. Overall, a diversity of intensities of pH and temperature effects on blood-O2 affinities was observed, which seems to be connected to the biological characteristics of the analysed species. Thermal disturbances in their habitats, likely to occur due to the global warming, would impair blood-O2 binding and unloading in some of the analysed fish species. Copyright © 2016 John Wiley & Sons, Ltd.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".