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Record W4392494427

Adhérence des chaussées : de l'étude cognitive aux applications

2010· preprint· en· W4392494427 on OpenAlexaboutno aff
Minh Tan Do

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2010
Typepreprint
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyChemistryComputer science
DOInot available

Abstract

fetched live from OpenAlex

The paper describes a synthesis of works conducted by the author in the field of high performance concretes and road skid resistance. Conducted as part of a PhD thesis at the University of Sherbrooke (Canada), the research on the fatigue behavior can characterize high performance concretes - both in terms of materials and structural elements - and compared with normal concrete. The analysis of fatigue life using concepts in reliability can calculate failure probability, indicator more relevant than the average fatigue life. Road skid resistance is ¾ of the research of the author, as a researcher and then team leader and project . The areas covered range of influential factors of skid resistance, including the road surface microtexture, to use the knowledge of available skid resistance - especially when it is degraded - to warn the driver, including also important aspects like the skid resistance evolution with the traffic and the European harmonization of measurement methods. This gradual progression help to deal with skid resistance from its cognitive (understanding, modeling) to applications, and to tackle with the laboratory-to-road transition and the scale change issues. This career of 20 years allowed the author to capture different aspects of research coordination such as project proposals, the development of partnerships - with a strong emphasis on international collaborations, supervision of researchers or management of a laboratory. Independent at first, these bricks were then structured to build a methodology of research coordination. Research perspectives for the future (4-5 years) are also identified to fill perceived gaps in this synthesis.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.243
Teacher spread0.227 · 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 teacher head, not a consensus.

Study designOther design
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

Citations0
Published2010
Admission routes1
Has abstractyes

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