Bibliographic record
Abstract
Background: An estimated 3% of all newborns with congenital heart disease develop hypoplastic left heart syndrome (HLHS), making it a prominent cause of mortality in this group if surgical procedures or a heart transplant are not implemented. While compelling evidence supports a genetic element, identifying a particular genetic cause is limited to a subgroup of patients, indicating a complex and multifaceted origin for this condition. The objective of this scientific contribution was to identify, synthesize, and analyze the scientific knowledge produced regarding the implications of researching on HLHS in a scoping review. Methods: The search for articles was diligently conducted between January 1, 2019 and February 20, 2025 on the PubMed/MEDLINE, Scopus, Web of Science, and Cochrane databases. This search was assiduously complemented by a gray search. It included internet browsers (e.g., Google) and medical textbooks. The following research question steered our study: "What are the basic data on the etiology and pathogenesis on HLHS?" All stages of the selection process were iwis carried out by the single author. Results: ) mice. Conclusions: HLHS is a complex and complicate congenital heart disease, which requires further investigation. In this article, I further explore the involvement of the endocardium in the progression of ventricular hypoplasia, therefore offering a potential explanation for the morphological alterations observed in the disease as a result of compromised blood flow to the developing ventricle. These findings may support a new paradigm for the complicated genetics of this congenital heart defect and there is some evidence that HLHS can originate genetically in a combinatorial approach.
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".