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Record W2936218806

Escale à Montréal : Le meilleur pour un court séjour Ed. 2

2014· book· fr· W2936218806 on OpenAlexaboutno aff
Collectif Collectif

Bibliographic record

VenueUlysse (Guides de voyage) eBooks · 2014
Typebook
Languagefr
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Le guide Escale a Montreal est l’outil ideal pour tirer le maximum d’un court sejour dans la metropole quebecoise. Pratique de par son format et l’organisation de son contenu ou l’on trouve l’essentiel en un coup d’oeil, ce guide se veut aussi agreable a consulter grâce a sa mise en page en couleurs, vivante et coloree. Au moyen d’une structure facile a comprendre en un clin d’oeil et a utiliser sur place, ce guide se veut ultra-pratique. Ainsi, une premiere section intitulee «Le meilleur de Montreal» met en lumiere ce que la ville a de mieux a offrir et facilite l’organisation generale de l’escapade. La section «Explorer Montreal» propose ensuite 10 itineraires cles en main pour ne rien manquer des differents quartiers de la ville. Pour chaque itineraire, un plan double-page clair et precis indique le trace du circuit, en plus de localiser attraits, cafes, restaurants, bars, boites de nuit, salles de spectacle, boutiques et hotels. Impossible de louper quoi que ce soit! Qui plus est, un systeme d’etoiles et de labels coup de coeur guide le lecteur vers les adresses qui se demarquent. Le chapitre «Montreal pratique», bourre de renseignements utiles livres de maniere succincte et aisement reperable, complete l’ouvrage. A tout cela s’ajoutent des cartes additionnelles sur les rabats de la couverture - vue generale de la ville, zoom sur le centre-ville, plan du metro de Montreal.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient 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 score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.020
GPT teacher head0.259
Teacher spread0.239 · 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
Published2014
Admission routes1
Has abstractyes

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