MétaCan
Menu
Back to cohort
Record W4238570748 · doi:10.1016/s1369-7021(03)00014-2

Canada breaks new groud

2003· article· en· W4238570748 on OpenAlexaboutno aff

Bibliographic record

VenueMaterials Today · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

UK study focuses on inhalation concernsThe National Science Foundation has made two fiveyear awards, to September 2008 (with a possible five-year renewal), as part of its program to create Nanoscale Science and Engineering Centers (NSEC): * $12.5 million for Nano-Chemical-Electrical-Mechanical Manufacturing Systems (Nano-CEMMS), a collaboration between sponsor University of Illinois at Urbana-Champaign, the California Institute of Technology, and the North Carolina Agricultural and Technical State University.It will build on two breakthroughs -very large scale integrated (VLSI) fluidic circuits can build arrays of addressable molecular gates, which can be digitally switched to dispense attoliter quantities -to develop new methodologies and tools for scalable, robust manufacturing of three-dimensional (3D) nanostructured multi-material devices.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.190
Threshold uncertainty score0.635

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0250.005
Scholarly communication0.0170.003
Open science0.0020.005
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.1900.027

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 head0.018
GPT teacher head0.271
Teacher spread0.253 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2003
Admission routes1
Has abstractno

Explore more

Same venueMaterials TodaySame topicArctic and Russian Policy StudiesFrench-language works237,207