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
Λny tool that man develops has potential flaws, whether we choose to recognize them or not. The concept of evidence-based medicine (EBM), along with its established "gold standard," the N-ple blind randomized control trial (RCT), is no different. In clinical medicine, when we wish to ask a scientific question, such as the effectiveness of a medication or product, we conduct studies on a patient population. These studies are organized via a variety of different methods; the best regarded among them are what is called RCT. We call EBM the compilation and application of the information gathered from different studies, so as to obtain the best possible outcome for a patient population. Within the sphere of EBM, there are different classifications that are used to inform clinicians on how strongly regarded a concept may be (e.g., "aspirin should be used with anyone suspected of having a heart attack" is highly regarded). The classifications are often directly linked with the type of study or analysis; data resulting from RCTs are considered among the strongest form of EBM, second only to meta-analyses, which is the compilation of several RCTs.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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