Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Brain metastases are an important clinical problem. Few animal models exist for melanoma brain metastases; many of which are not clinically relevant. Longitudinal MRI was implemented to examine the development of tumors in a clinically relevant mouse model of melanoma brain metastases. Fifty thousand human metastatic melanoma (A2058) cells were injected intracardially into nude mice. Three Tesla MRI was performed using a custom-built gradient insert coil and a mouse solenoid head coil. Imaging was performed on consecutive days at four time points. Tumor burden and volumes of metastases were measured from balanced steady-state free precession image data. Metastases with a disrupted blood-tumor barrier were identified from T1-weighted spin echo images acquired after administration of gadopentetic acid (Gd-DTPA). Metastases permeable to Gd-DTPA showed signal enhancement. The number of enhancing metastases was determined by comparing balanced steady-state free precession images with T1-weighted spin echo images. After the final imaging session, ex-vivo permeability and histological analyses were carried out. Imaging showed that both enhancing and nonenhancing brain metastases coexist in the brain, and that most metastases switched from the nonenhancing to the enhancing phenotype. Small numbers of brain metastases were enhancing when first detected by MRI and remained enhancing, whereas other metastases remained nonenhancing to Gd-DTPA throughout the experiment. No clear relationship existed between the permeability of brain metastases and size, brain location and age. Longitudinal in-vivo MRI is key to studying the complex and dynamic processes of metastasis and changes in the blood-tumor barrier permeability, which may lead to a better understanding of the variable responses of brain metastases to treatments.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it