MétaCan
Menu
Back to cohort
Record W2018509468 · doi:10.3166/jesa.37.1059-1074

Méthodes ensemblistes pour l'étalonnage géométrique

2003· article· fr· W2018509468 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2003
Typearticle
Languagefr
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsInterval (graph theory)MathematicsMeasure (data warehouse)Dimension (graph theory)CalibrationPessimismSet (abstract data type)AlgorithmComputer scienceStatisticsPhilosophyCombinatoricsData miningEpistemology

Abstract

fetched live from OpenAlex

This paper presents first results on robot manipulators calibration performed by in- terval constraints propagation. This method gives an interval domain which confine each pa- rameter. This interval width depends on measure precision, modelling errors and set estimation pessimism. This application shows that it is possible to compute large dimension non-linear problems with interval methods. MOTS-CLES : analyse par intervalles, calcul ensembliste, etalonnage des robots, estimation en- sembliste, methode garantie, propagation de contraintes, robotique.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.055
GPT teacher head0.312
Teacher spread0.257 · 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