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Record W2015387662 · doi:10.1081/lft-200043681

Laser Based Detection of Paraffin in Crude Oil Samples: Numerical and Experimental Study

2006· article· en· W2015387662 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

VenuePetroleum Science and Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCrude oilMaterials scienceChromatographyAnalytical Chemistry (journal)ChemistryPetroleum engineeringGeology

Abstract

fetched live from OpenAlex

Abstract A laser spectroscope was used to detect paraffin in paraffin contaminated oil samples. After passing through the oil sample, the laser light was detected by using a semi-conductor photodiode, which in turn converts the light signal into electric voltage. The samples studied have paraffin concentrations ranging from 20–60% wt and a thickness of 1–10 mm. The results showed a good agreement with Beer Lambert's Law for the attenuation of light. A 1-D mathematical model based on energy balance and describing the process of laser radiation attenuation within the oil sample was developed and numerically solved. The model was used to predict the net laser light and the amount of light absorbed per unit volume at any point within the oil sample. The results of the numerical model were found to be in correlation with those obtained from the experiments. The mathematical model presented was then used for different types of oil products to determine the local rate of absorption in an oil layer under differen...

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 score0.040
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.223
Teacher spread0.216 · 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