Assemble Local Evidence on Context and Current Practices
Bibliographic record
Abstract
The Assemble Local Evidence on Local Context and Current Practice Phase is intended to increase understanding of the magnitude of issue/problem within the local context, determine how it is being addressed in day-to-day practice, and measure the evidence-practice gap. Pertinent questions that drive the enquiry into local evidence are: What is the context for the practice issue? How many (and what proportion of) individuals have the condition of interest? What is the demographic and clinical profile of these individuals? What is known about current practice (the care these individuals receive) and the outcomes produced by current practice? What healthcare providers are addressing the concern? What types of healthcare providers are providing care? What are the providers' scopes of practice? What are the resource implications of providing care for these individuals currently (what does it cost)? What is the extent of the evidence-practice gap?
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 | 0.233 | 0.544 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.029 | 0.019 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".