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Record W2121736670 · doi:10.1145/2318836.2318840

An automatic control interface for network-accessible embedded instruments

2012· article· en· W2121736670 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACM SIGBED Review · 2012
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsMcGill University
FundersCanada Research ChairsMcGill UniversityCanadian Institute for Advanced Research
KeywordsJSONPython (programming language)Computer scienceInterface (matter)User interfaceProgramming languageControl networkSource codeNetwork interfaceOperating systemEmbedded systemControl (management)SoftwareArtificial intelligence

Abstract

fetched live from OpenAlex

We describe a metaprogrammed control interface and support library for network-accessible embedded systems. Together, this project permits functions written in standard C code to be exposed via a network interface expressed in JSON. In turn, this JSON interface mates with a Python library that provides a high-level, user-friendly, and expressive development environment. This control interface removes the need to explicitly code interactions at the Python and network layers. As a result, the volume of error-prone and redundant hand-written code (e.g. for error-checking and validation) is vastly reduced.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score0.932

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 head0.016
GPT teacher head0.309
Teacher spread0.293 · 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