Bibliographic record
Abstract
he SSH Open Marketplace is one of the key exploitable results of the SSHOC project. It is designed to be a central information hub where researchers can go to find detailed information about software tools, relevant publications, datasets and workflows. Within the Marketplace contextualisation should be provided, linking, for example, publications to the tools or datasets they mention. This deliverable, D7.3 Marketplace Interoperability, focuses on the process of populating the SSH Open Marketplace, thereby complementing the deliverables on the technical implementation (D7.2 Marketplace Implementation) and the curation (D7.4 Marketplace Data Population and Curation) of the Marketplace. In the beginning of the SSHOC project a list of potential sources that could be added to the new SSH Open Marketplace was compiled. During the first phase of the project, each source in this list was then investigated regarding its potential to be added to the Marketplace. This deliverable details how the selection process of potential sources worked. Each of the potential sources will be described briefly, it will be highlighted why they would be of interest to be added to the Marketplace and discussed whether the decision was made to ingest them into the Marketplace during the run-time of the SSHOC project. The document is structured by the decision made for each specific source, starting with a section of all the sources that have already been ingested in the Marketplace by the time of writing. This is followed by the sources that were decided to be ingested in the course of the project and that are currently in the process of being ingested. Then the sources are listed that were considered but discarded for one reason or another (e.g. poor quality of metadata, not enough new, unique items) and finally there is a section with sources that would be great additions but cannot be easily ingested using the automatic ingestion pipelines that are currently available. These sources might later be considered for manual inclusion into the Marketplace. This document also provides an overview table showing for each source how many individual items have been or will likely be ingested into the Marketplace and whether the source will be ingested only once or is considered for continuous ingestion, because it is expected that there will be frequent updates at the source that should also be reflected in the Marketplace. At the end of the document there is also a section discussing possible future steps that could be taken to improve the quality of the Marketplace after the project has ended.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 0.030 |
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; both teacher heads agree on what is shown here.
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".