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Record W2334536420 · doi:10.1785/gssrl.74.6.817

SSA 2003 Annual Meeting Presidential Address: Reflections on the Role of Technology in Seismology

2003· article· en· W2334536420 on OpenAlexaffabout
Gail M. Atkinson

Bibliographic record

VenueSeismological Research Letters · 2003
Typearticle
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCitationIconPresidential systemDownloadLibrary sciencePrivilege (computing)Political scienceWorld Wide WebHistoryOperations researchComputer scienceMedia studiesEngineeringSociologyLawPolitics

Abstract

fetched live from OpenAlex

Research Article| November 01, 2003 SSA 2003 Annual Meeting Presidential Address: Reflections on the Role of Technology in Seismology Gail Atkinson Gail Atkinson Department of Earth Sciences Carleton University Ottawa, ON Canada K1S 5B6 Search for other works by this author on: GSW Google Scholar Seismological Research Letters (2003) 74 (6): 817–819. https://doi.org/10.1785/gssrl.74.6.817 Article history first online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation Gail Atkinson; SSA 2003 Annual Meeting Presidential Address: Reflections on the Role of Technology in Seismology. Seismological Research Letters 2003;; 74 (6): 817–819. doi: https://doi.org/10.1785/gssrl.74.6.817 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search Let me begin by saying how much I have appreciated the opportunity to be President of SSA these last two years. It has been a pleasure and a privilege to work with our dedicated SSA staff and Board of Directors, and our talented membership of seismologists. It is customary at this time, as I pass the baton to the next SSA president, to make some remarks on a favorite topic that affects the practice or the future of seismology. I take this opportunity to offer some reflections on how technology influences the way we do our work in seismology. As... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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 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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.063
GPT teacher head0.349
Teacher spread0.286 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2003
Admission routes2
Has abstractyes

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