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Record W4386387794 · doi:10.52340/ns.2022.25

Some of 2021 nanoforums: ANM, ICANM, IMS, GTU nano, and HMT

2023· article· en· W4386387794 on OpenAlexaboutno aff
Levan Chkhartishvili

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndustrial Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsLibrary scienceExhibitionPolitical scienceGeographyArchaeologyComputer science

Abstract

fetched live from OpenAlex

Some of 2021 nanoforums: ANM, ICANM, IMS, GTU nano, and HMT. / L. Chkhartishvili. – 2021–2022. – # 21/22. – pp. 309-322. – geo. There are given chronicles for five 2021 nanoforums: 17th International Conference on Advanced Nanomaterials, 2021 July 22 – 24, Aveiro, Portugal (ANM 2021); 8th International Conference and Exhibition on Advanced and Nanomaterials, 2021 August 9 – 11, Ottawa, Canada (ICANM 2021); 4th International Conference “Modern Technologies and Methods of Inorganic Materials Science”, 2021 September 20 – 21, Tbilisi, Georgia (IMS 2021); 6th International Conference “Nanotechnology” 2021 October 4 – 7, Tbilisi, Georgia (GTU nano 2021); and 7th International Materials Science Conference High Mat Tech, 2021 October 5 – 7, Kyiv, Ukraine (HMT 2021). Fig. 29.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.544
Threshold uncertainty score0.650

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.5440.356

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 head0.010
GPT teacher head0.189
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), not a consensus.

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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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