Bibliographic record
Abstract
BACKGROUND: The BioMoby project aims to identify and deploy standards and conventions that aid in the discovery, execution, and pipelining of distributed bioinformatics Web Services. As of August, 2006, approximately 680 bioinformatics resources were available through the BioMoby interoperability platform. There are a variety of clients that can interact with BioMoby-style services. Here we describe a Web-based browser-style client--Gbrowse Moby--that allows users to discover and "surf" from one bioinformatics service to the next using a semantically-aided browsing interface. RESULTS: Gbrowse Moby is a low-throughput, exploratory tool specifically aimed at non-informaticians. It provides a straightforward, minimal interface that enables a researcher to query the BioMoby Central web service registry for data retrieval or analytical tools of interest, and then select and execute their chosen tool with a single mouse-click. The data is preserved at each step, thus allowing the researcher to manually "click" the data from one service to the next, with the Gbrowse Moby application managing all data formatting and interface interpretation on their behalf. The path of manual exploration is preserved and can be downloaded for import into automated, high-throughput tools such as Taverna. Gbrowse Moby also includes a robust data rendering system to ensure that all new data-types that appear in the BioMoby registry can be properly displayed in the Web interface. CONCLUSION: Gbrowse Moby is a robust, yet facile entry point for both newcomers to the BioMoby interoperability project who wish to manually explore what is known about their data of interest, as well as experienced users who wish to observe the functionality of their analytical workflows prior to running them in a high-throughput environment.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.052 |
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".