MétaCan
Menu
Back to cohort

Композиционные тензорезистивные материалы на основе матрицы полибензимидазола

2019· article· ru· W4248407780 on OpenAlexaff
В. А. Кузнецов, Б.Ч. Холхоев, В.Г. Макотчеко, А.Н. Лавров, Е.Н. Горенская, А.С. Бердинский, В.Ф. Бурдуковский, А.И. Романенко, В.Е. Федоров

Bibliographic record

VenueNanoindustry Russia · 2019
Typearticle
Languageru
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Изучены пленочные композиционные материалы на основе полимерной матрицы полибензимидазола с наноструктурированными углеродными наполнителями. В качестве полимерной матрицы использовался поли-2,2’-п-оксидифенилен-5,5’-дибензимидазолоксид (ОПБИ) с наполнителями – графитовыми нанопластинами и малослойным графеном. Экспериментально изучен тензорезистивный эффект и температурные зависимости электросопротивления образцов, найдены коэффициент тензочувствительности и усталостная прочность. В пределах погрешности коэффициент тензочувствительности не зависит от концентрации наполнителя (в среднем 15 для МСГ и 13 для ГНП). Тензочувствительность образцов стабильна до 100 тыс. знакопеременных циклов нагрузки. Основной вклад в сопротивление вносят диэлектрические полимерные прослойки между Si-наночастицами наполнителя, а проводимость обусловлена туннелированием между частицами.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0180.013

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 head0.009
GPT teacher head0.204
Teacher spread0.196 · 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
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueNanoindustry RussiaSame topicMilitary Technology and StrategiesFrench-language works237,207