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Record W4301721876 · doi:10.5281/zenodo.6963541

D.2.2.3. At least four among video spots or clips in various languages

2022· report· en· W4301721876 on OpenAlexaff
Laura Caciagli, Paola Agostini, Tomislav Budić, Davor Deželjin, Sabrina D'Ambrosio, Gianandrea Mannarini, Maria Mihalić, Josip Orović, Zoran Pavin, Evangelia Piteni, Sabina Rako Juravić, Martin Zrilic

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typereport
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsCLIPSSpotsComputer scienceComputer graphics (images)Artificial intelligenceChemistry

Abstract

fetched live from OpenAlex

The GUTTA project aims and results were disseminated through the realization of several videos (11), the majority of them (9) published on the CMCC YouTube Channel and organized in a playlist1<br> The two remaining videos were live streamed and published on the Adsp-MAM’s Facebook page2 More in detail, the LP coordinated the activities for the realization of the final video of the project, being involved in the design and realization of the script and storyboard of the videos; in the realization of the texts, in English and in Italian, to be used by the speakers of the videos. Moreover, LP supported the video-maker in the iconographic research and in the editing of the videos. The text for the subtitles of the English version – subtitled in Croatian of the video was translated by MPPI, GUTTA project partner. The University of Zadar and CSA mare nostrum contributed to the realization of the GUTTA final videos by providing footages and photos.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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: Other · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0020.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.2650.009

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 head0.065
GPT teacher head0.278
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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