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Record W4205141949 · doi:10.26717/bjstr.2021.40.006465

Review of Temperature Measurement Techniques

2021· article· en· W4205141949 on OpenAlexaboutno aff
Omar Chaalal

Bibliographic record

VenueBiomedical Journal of Scientific & Technical Research · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsnot available
Fundersnot available
KeywordsAbu dhabiEngineeringLibrary scienceGeographyArchaeologyComputer science

Abstract

fetched live from OpenAlex

Husain Al Hashimi1, Omar Chaalal2*, Marouane Chaalal3 and Hameed Muhamed4 Author Affiliations 1Consultant Mechanical Engineering, UAE 2Abu Dhabi University College of Engineering, Chemical Engineering, UAE 3Engineer Fluor Gulf Plant, UAE 4Sheridan College, Canada Received: December 01, 2021 | Published: December 13, 2021 Corresponding author: Omar Chaalal, Abu Dhabi University College of Engineering, Chemical Engineering, UAE DOI: 10.26717/BJSTR.2021.40.006465

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.005

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 head0.106
GPT teacher head0.401
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2021
Admission routes1
Has abstractyes

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