Bibliographic record
Abstract
Electrocardiography data obtained in diabetic and age-matched control rats using Bioamp (ADInstruments, Dunedin, New Zealand), 3 weeks after induction of diabetes. Transthoracic echocardiography was performed in diabetic and age-matched control rats using VEVO 2100 (Visual Sonics, Toronto, ON, Canada) equipped with a 40-MHz transducer, 2 weeks after diabetes induction. For histological data, prepared sections were observed under microscopy (Leica Application suite). Magnification was set up at ×400. Micrographs were used to calculate the collagen content in the myocardial interstitium using the Image J software as the percentage of red-stained area in the section. An average of 15-20 images from each animal from each group was analyzed. To evaluate the perivascular fibrosis of intramyocardial arterioles of the ventricles, arterioles with a diameter between 100-200 μm were chosen. For each image of the arteriole, a region of interest was delimited around it to exclude areas of interstitial collagen which were not related to the arteriole. Perivascular fibrosis was determined by the ratio between the area occupied by collagen stained with picro-sirius within the region of interest and the area of the lumen. The software Image J was used to calculate the area occupied by the collagen and to mark the regions of interest, and the software Zen (Zeiss, Germany) to calculate the area of the lumen. The images were obtained with a 20x magnifying objective (Eclipse TE 300, Nikon, USA) with a digital camera (AxioCam, Zeiss, Germany).
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".