MétaCan
Menu
Back to cohort
Record W2324912272 · doi:10.1149/2.0171510jss

Micro-Nano Systems in Health Care and Environmental Monitoring

2015· article· en· W2324912272 on OpenAlex
Ajit Khosla, Peter J. Hesketh

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.

Bibliographic record

VenueECS Journal of Solid State Science and Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicMolecular Communication and Nanonetworks
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceEnvironmental monitoringNano-Systems engineeringHealth careNanotechnologyEnvironmental scienceEnvironmental engineeringEngineeringPolitical science

Abstract

fetched live from OpenAlex

This focus issue is devoted to Micro-Nano Systems in Health Care and Environmental Monitoring. It has been an exciting opportunity to collect together papers from invited speakers and authors who participated in the related symposium held at the 227th ECS meeting in Chicago in May 2015. This meeting brought together medical professionals, clinicians, engineers, chemists, biologists and physicists under the same roof. This symposium and the papers published in the focus issue provide for a synopsis of the research, development, and technological evolution of micro-nano sensors and systems in healthcare and environmental monitoring applications.

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)0.000
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 score0.305
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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