Anaemia: Adaptive Mechanisms and Consequences
Bibliographic record
Abstract
Abstract Human life depends on the availability of oxygen and its conversion into energy used by living cells. Reduced oxygen to tissues is referred to as hypoxia, and may result from decreased oxygen delivery or mitochondrial dysfunction. In the setting of tissue hypoxia due to anaemia or other causes, several adaptive and coordinated physiologic processes are initiated to maintain oxygen delivery and limit oxygen consumption. Mechanisms to increase oxygen delivery in the face of anaemia or global hypoxia include the stimulation of erythropoiesis, and increasing cardiac output. Oxygenation availability is further maximised by decreases in the haemoglobin‐oxygen binding affinity, increases in tissue oxygen extraction, and via changes in regional blood flow. Mild to moderate anaemia, especially if chronic, is generally well tolerated given these adaptive processes. In states of inflammation or chronic disease, down regulation of haemoglobin occurs and may represent an important adaptive mechanism. Key Concepts: Aerobic metabolism and human life depend on the availability of oxygen. Anaemia results when the haemoglobin levels are below normal and, if severe, may result in tissue hypoxia. Adaptive mechanisms exist to compensate for anaemia or other causes of tissue hypoxia so that oxygen delivery is maintained and balanced with oxygen consumption. A major adaptive mechanism in response to anaemia is to increase production of the growth hormone erythropoietin, leading to the formation of red blood cells. The anaemia associated with inflammation has features of an adaptive response, is generally well tolerated and rarely requires treatment.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".