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Summary of Work On development and characterization of improved Materials

2021· report· en· W3166648777 on OpenAlexaff
Stefan Gschwander, Ana Lázaro, Mónica Delgado, Christoph Rathgeber, Michael Brütting, Stephan Höhlein, Melissa Obermeyer, Dominic Groulx, Thomas Haussmann, Daniel Lager, Saman Nimali Gunasekara, Mohammed Farid, Juan de Dios Cruz Elvira, Gonzal Diarce, Gerald Englmair, Thomas Aigenbauer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCharacterization (materials science)Work (physics)InstitutionDevelopment (topology)Construction engineeringEngineering ethicsEngineeringNanotechnologyMaterials scienceMechanical engineeringSociologyMathematicsSocial science

Abstract

fetched live from OpenAlex

As the material development is done at different institution the objective of the work was to collect the materials which are under research and development to get an overview on the most relevant properties of these materials and application which are addressed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.286
Teacher spread0.229 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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