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Record W4309144556 · doi:10.26443/seismica.v1i1.255

The launch of Seismica: a seismic shift in publishing

2022· article· en· W4309144556 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSeismica · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsMcGill University
FundersMcGill University
KeywordsPublishingPublic relationsLibrary sciencePolitical scienceBusinessComputer scienceLaw

Abstract

fetched live from OpenAlex

Seismica, a community-run Diamond Open Access (OA) journal for seismology and earthquake science, opened for submissions in July 2022. We created Seismica to support a shift to OA publishing while pushing back against the extreme rise in the cost of OA author processing charges, and the inequities this is compounding. Seismica is run by an all-volunteer Board of 47 researchers who fulfil traditional editorial roles as well as forming functional teams to address the needs for technical design and support, copy editing, media and branding that would otherwise be covered by paid staff at a for-profit journal. We are supported by the McGill University Library (Québec, Canada), who host our website and provide several other services, so that Seismica does not have any income or financial expenditures. We report the process of developing the journal and explain how and why we made some of the major policy choices. We describe the organizational structure of the journal, and discuss future plans and challenges for the continued success and longevity of Seismica.

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.335
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it