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Record W2288565797 · doi:10.5555/2888619.2888644

Evaluating the science-technology interaction in nanotechnology: a simulation-based study

2015· article· en· W2288565797 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWinter Simulation Conference · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicComplex Network Analysis Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsInterconnectivityMultidisciplinary approachContext (archaeology)Knowledge managementProductivityNanotechnologyField (mathematics)Sociology of scientific knowledgeEngineeringComputer scienceData scienceSociologySocial scienceMaterials scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Nanotechnology as an emerging, science-driven and rapidly evolving field with the multidisciplinary nature is an example of cases where science and technology are proximate and their interaction is essential. The scientific and technological networks can be formed separately in a social context and the linkages from the scientific to the technological network can be established through authors-inventors who act as gatekeepers and bridge the knowledge between the two communities. This work concerns individual researchers who are doing both, patenting and publishing, in the field of nanotechnology in Quebec Canada. An agent-based model was developed using real data regarding both nano-related articles and their authors, and nano-related patents and their inventors were collected from SCOPUS and USPTO databases respectively. While the repetitiveness in collaborative relationships has shown an enhancement in author-inventors performance, it negatively affects the knowledge flow efficiency. Author-inventors are fundamentals for increasing the network productivity and assure its interconnectivity.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.138
GPT teacher head0.431
Teacher spread0.294 · 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