Introducing the Initiative for Open Abstracts (I4OA)
Bibliographic record
Abstract
Initiative for Open Abstracts Launches to Promote Discovery of Research A new cross-publisher initiative calls for unrestricted availability of abstracts to boost the discovery of research The Initiative for Open Abstracts (I4OA) calls on scholarly publishers to open their abstracts, and specifically to deposit them with Crossref. Unrestricted availability of abstracts will boost the discovery of research. 40 publishers have already agreed to support I4OA and to make their abstracts openly available. I4OA is also supported by a large number of research funders, libraries and library associations, infrastructure providers, and open science organizations. The Initiative for Open Abstracts (I4OA) calls on all scholarly publishers to open the abstracts of their publications, and specifically to distribute them through Crossref, in order to facilitate large-scale access and promote discovery of critical research. I4OA—a collaboration between scholarly publishers, academic librarians, researchers, infrastructure providers and other stakeholders—will launch at the online conference of the Open Access Scholarly Publishers Association (OASPA) on September 24th 2020. I4OA has been established to advocate and promote the unrestricted availability of the abstracts of scholarly publications, particularly journal articles and book chapters. Making abstracts openly available helps scholarly publishers to maximize the visibility and reach of their journals and books. Open abstracts make it easier for scholars to discover, read and then cite these publications; promotes their inclusion in systematic reviews; expands and simplifies the use of text mining, natural language processing and artificial intelligence techniques in bibliometric analyses; and facilitates scholarship across all disciplines by those without subscription access to commercial bibliographic services. I4OA was inspired by the success of the Initiative for Open Citations (I4OC), which encourages the submission of references to Crossref. Since the launch of I4OC in 2017, over two thousand scholarly publishers have chosen to make the reference lists of their journal articles and book chapters openly available through Crossref. I4OA aims to replicate the success of I4OC by achieving a rapid jump in the open availability of scholarly abstracts. Contact & further information Further information may be obtained from the I4OA website at https://i4oa.org (live from September 24th 2020), by emailing Ludo Waltman, coordinator of I4OA, at openabstracts@gmail.com, or by following @open_abstracts on Twitter. There will be also a webinar on I4OA on October 5th 2020 at 4 pm CEST (register at https://tinyurl.com/i4oa-webinar),
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 | 0.151 | 0.288 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.043 | 0.055 |
| Open science | 0.007 | 0.049 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.097 | 0.100 |
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".