MétaCan
Menu
Back to cohort
Record W4300646871 · doi:10.31399/asm.cp.itsc2001p0705

Ensemble In-Flight Particle Diagnostics Under Thermal Spray Conditions

2001· article· en· W4300646871 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThermal spray · 2001
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsPyrometerTemperature measurementThermal sprayingMaterials scienceParticle (ecology)PlasmaComputational physicsJet (fluid)Particle velocityAcousticsMechanicsPhysicsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Abstract The Accuraspray is a new in-flight particle sensor that provides information on the average in-flight particle temperature, using two-color pyrometry, and velocity, using a cross-correlation calculation. Various aspects influencing the reliability of the sensor estimates are studied. First, the sensitivity of the temperature and velocity estimates to the positioning of the sensor with respect to the particle jet, such as the angular orientation of the fibers and the working distance to the spray plume, is evaluated. Then, the influence of the plasma radiation on the temperature measurement is estimated. This influence can be reduced significantly by filtering out the low frequency components of the pyrometric signals, which contain most of the plasma fluctuations. Finally, a lower limit in the signal-to-noise ratio (SNR), for which an acceptable temperature estimate is obtained, is evaluated. A valid velocity estimate can still be obtained with a lower SNR. All these studies were performed under various spraying conditions, including plasma spraying and HVOF, using various feedstock materials (YSZ, Al-Si, cermets).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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