Cloud-based Meta-analysis to Bridge Science and Practice: Welcome to metaBUS
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
Although volumes have been written on spanning the science-practice gap in applied psychology, surprisingly few tangible components of that bridge have actually been constructed. We describe the metaBUS platform that addresses three challenges of one gap contributor: information overload. In particular, we describe challenges stemming from: (1) lack of access to research findings, (2) lack of an organizing map of topics studied, and (3) lack of interpretation guidelines for research findings. For each challenge, we show how metaBUS, which provides an advanced search and synthesis engine of currently more than 780,000 findings from 9,000 studies, can provide the building blocks needed to move beyond engineering design phase and toward construction, generating rapid, first-pass meta-analyses on virtually any topic to inform both research and practice. We provide an Internet link to access a preliminary version of the metaBUS interface and provide two brief demonstrations illustrating its functionality.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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