Développement d’une nouvelle génération de capteurs de gaz. Conséquences environnementales DEVELOPMENT OF A NEW GENERATION OF GAS SENSORS. ENVIRONMENTAL CONSEQUENCES
Bibliographic record
Abstract
Ce rapport presente les differentes technologies de detection des gaz dangereux pour l'homme et l'environnement actuellement sur le marche. Il identifie les avantages et les inconvenients de ces differentes technologies pour permettre a l'utilisateur de faire un choix en fonction de son contexte d'utilisation. Beaucoup d’applications utilisent ce genre de detecteur, mais leur developpement necessite l’amelioration de leurs performances. Cote industriel, le marche global des capteurs chimiques connait une tres forte progression (+9,6%/an) depuis la fin des annees 2000 avec un volume de 15 milliards de dollars en 2010. Concernant le marche pour les equipements de detection de gaz evalue dans un rapport recent de Global Industry Analysts Inc., il est estime a 1,24 milliards de dollars US en 2008 et devrait atteindre 1,5 milliards de dollars en 2012. Ce marche, en constante evolution depuis le debut des annees 90, est partage en grande partie entre l’Amerique du Nord (USA et Canada) et l’Europe. Ceci etant, avec la rapide industrialisation de pays emergents asiatiques et sud-americains, ce marche promet un essor spectaculaire surtout avec la forte demande due aux preoccupations de notre temps en matiere d’environnement, de securite et de controle des procedes. Ces dispositifs de detection offrent potentiellement des applications dans les principaux domaines qui sont le transport, l’environnement, la sante, l’industrie et l’agroalimentaire. This report presents the different detection technologies of gases hazardous to humans and the environment currently on the market. It identifies the advantages and disadvantages of these technologies to allow the user to make a choice based on its context of use. Many applications use this type of detector, but their development requires improving their performance. On the industrial side, the global market for chemical sensors is experiencing very strong growth (+9.6%/year) since the late 2000s with a volume of $15 billion in 2010. Concerning the market for gas detection equipment evaluated in a recent report by Global Industry Analysts Inc., it is estimated at $1.24 billion in 2008 and should reach $1.5 billion in 2012. This market, evolving constantly since the early 90s, is largely shared between the North America (USA and Canada) and Europe. That being said, with the rapid industrialization of emerging Asian and South American market, this market promises a dramatic growth especially with the high demand due to current concerns in terms of environment, security and process control. These sensing devices potentially offer applications to the main areas that are transportation, environment, health, industry and the food sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".