Bibliographic record
Abstract
Abstract The cardiovascular system is the most important organ system required for human life. Toxicity to the component parts of the cardiovascular system can lead to death or devastating irreparable damage to the normal functioning of the organ systems of the human body. Many industrial and pharmaceutical chemicals can exert toxic action on various components of the cardiovascular system. Chemicals that target the heart are classed as cardiotoxins and can exert their effects directly or indirectly. The dosage and exposure period influence the effects these chemicals may exert on the heart. Cardiotoxins can alter the heart functionally or structurally. Functional alterations, such as the induction of arrhythmias, affect the normal physiological performance of the heart. Cardiotoxins may also selectively induce structural damage by altering the heart's cellular components. Structural cardiotoxins may directly affect cardiomyocyte membrane integrity, ion transport and energy supply systems. Cardiotoxic agents, chemically classed as plant‐ and animal‐derived toxins, heavy metals, aliphatic alcohols and hydrocarbons, aldehydes, gases (CO), carcinogens, and pharmaceutical agents utilized in the treatment of cancer, high blood pressure (antihypertensive drugs), arrythmias and depression (tricyclic antidepressants), and anesthetics (such as bupivacaine and halogenated hydrocarbon anesthetics) and their mechanisms of toxicity are reviewed. Environmental pollutants, including particulate matter, polyaromatic hydrocarbons and metals, which are suspected cardiotoxic agents, are briefly highlighted.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.037 | 0.019 |
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".