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Record W7056687045

Gilbert Thibodeau, candidat à la mairie de Montréal

2017· other· fr· W7056687045 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2017
Typeother
Languagefr
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsIndian oceanSection (typography)Subject (documents)
DOInot available

Abstract

fetched live from OpenAlex

Revoyez la conférence vidéo qui fut organisée par le Mouvement républicain du Québec le 1er novembre dernier. Notre invité était M. Gilbert Thibodeau, candidat à la mairie de Montréal. Celui-ci s'est fait un plaisir de répondre aux questions des internautes en temps réel. Né à Montréal, Gilbert Thibodeau est commerçant et homme d’affaires. Il est diplômé de l’École des Hautes Études Commerciales de Montréal (HEC) et de l’Institut Canadien de Gestion. Il siège au conseil d’administration du Centre Nouvelle Approche Humanitaire d’Apprentissage (NAHA) bénévolement, à Montréal. Il a aussi siégé au conseil d’administration de l’Institut Canadien de Gestion, section de Montréal, de 1995 à 2011. Il en fut le président de 2007 à 2011. Gilbert Thibodeau possède une vaste expérience dans les activités reliées à la planification stratégiques d’entreprises, au développement des affaires, à la gestion du personnel et à l’implantation de systèmes évolués de gestion. Depuis longtemps il est engagé auprès des jeunes sportifs Montréalais, Québécois et Canadiens, notamment en ski alpin & acrobatique. - Adhérer au Mouvement républicain du Québec : https://www.mouvement-quebec.com . - Vous pouvez faire un don : https://www.paypal.me/mouvementQC .

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.307
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.3370.030

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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