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Makers of the Microchip

2011· article· en· W2106844896 on OpenAlexaffabout
Ben Li

Bibliographic record

VenueScience and Public Policy · 2011
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLibrary scienceMedia studiesPolitical scienceVolume (thermodynamics)SociologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

Journal Article Microchips are made of people Get access Lécuyer Christophe Brock David CMakers of the Microchip 2010Cambridge, MA MIT Press368US$24.95, ISBN 9780262014243 Ben Li Ben Li research associate Department of Communication and Culture, University of Calgary, SA 258, 2500 University Drive NW, Calgary, Canada T2N 1N4; Email: bali@ucalgary.ca Search for other works by this author on: Oxford Academic Google Scholar Science and Public Policy, Volume 38, Issue 3, April 2011, Pages 251–252, https://doi.org/10.3152/030234211X12924093660750 Published: 01 April 2011

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0080.009
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0390.008

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 head0.033
GPT teacher head0.228
Teacher spread0.195 · 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 designQualitative
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

Citations5
Published2011
Admission routes2
Has abstractyes

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