The Seismica initiative: a community-led Diamond Open Access journal for seismological research
Bibliographic record
Abstract
On 24 November 2020, the Springer Nature publishing group announced the introduction of Open Access (OA) journals in Nature and its sibling journals. The corresponding OA publication fee (charged directly to the authors) was set to €9,500/$11,390/£8,290, an amount that may be well out of reach for researchers with limited financial means. This is especially a problem for researchers in developing countries, and for early-career researchers on small, personal fellowships. Funding agencies often demand that research be published under an OA license, forcing authors to accept the high publication fees. The high cost of these and similar OA fees for other Earth science journals prompted a discussion among the seismological community on Twitter, during which the idea was raised to start a free-to-publish, free-to-read journal for seismological research. The concept of Diamond Open Access was previously adopted by Volcanica (www.jvolcanica.org) for volcanological research, providing a precedent and directives for similar initiatives (like Seismica, but also Tektonika for the structural geology community). Following the community discussion on Slack with over 100 participants, a small "task force" was formed to investigate in detail the possibility of starting a Diamond OA seismology journal, taking Volcanica as a model. In this contribution, we report the progress that has been made by the task force and the seismological community in the conceptualisation of the journal, and the steps that remain to be taken. Once the initiation of the journal is completed, Seismica will offer a platform for researchers to publish and access peer-reviewed work with no financial barriers, promoting seismological research in an inclusive manner. We invite all interested members of the seismological and earthquake community to participate in the discussions and development of this OA journal, by contacting the authors listed on this abstract.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.176 | 0.063 |
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".