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Record W4312014902 · doi:10.5281/zenodo.7464145

Deliverable D2.8 Revised use-cases for the FWCR Platform version 2.0 (PAR Cycle 2)

2021· report· en· W4312014902 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.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typereport
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsNutrasource
FundersHorizon 2020 Framework Programme
KeywordsDeliverableComputer scienceSystems engineeringEngineering

Abstract

fetched live from OpenAlex

The TURNkey concept model is being developed over three cycles of participatory action research (PAR). This report describes the process and findings of the 2nd PAR cycle in the TURNkey project. In light of these findings, the report reviews the end-user use cases that were developed for TURNkey during the 1st PAR cycle (which have been reported in D2.6) and revises them in light of the discussions with end-users and TURNkey scientists, engineers and software developers that occurred during the 2nd PAR cycle. The report lays the foundation for the 3rd and final round of PAR that will be conducted for TURNkey. It will also inform TURNkey deliverable D7.7, which will provide end-users with an (exemplar) model Business Continuity and Resilience Plan (BCRP) and Disaster Management Plan (DMP) framework for integrating the TURNkey FWCR platform into their disaster management planning process. This report provides the following: Review of the key lessons from the 1st PAR Cycle Online workshops with potential end-users using a virtual demonstrator (process and findings) SWOT analysis with TURNkey scientists and engineers (process and findings) TURNkey application workshop around a hypothetical hospital scenario (process and findings) Consortium-wide reflection on findings from the 2nd PAR Cycle (process and findings) Revised end-user use cases Revised table of TURNkey features, what end-users want vs what is possible and in scope A revised version of the FWCR concept model A conclusion and next steps

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0040.001
Open science0.0030.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.102
GPT teacher head0.276
Teacher spread0.175 · 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