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Record W7132885293

Evaluation of two automated methods for determination of the air void system parameters of hardened concrete

2006· dissertation· W7132885293 on OpenAlexfundno aff
Amir Mohammad Ramezanianpour

Bibliographic record

VenueTSpace · 2006
Typedissertation
Language
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsScannerVoid (composites)Automated methodTest methodNational standardAutomationDigital image analysis
DOInot available

Abstract

fetched live from OpenAlex

Determination of air void parameters of hardened concrete is usually performed according to ASTM C 457 standard. This standard process is tedious and the results depend on the skill of the operator. Several researchers have proposed alternative automated methods for performing the test. Two of these new methods are Rapid Air 457 and the scanner method. Rapid Air 457 collects images from the surface of concrete samples using a digital microscope whereas in the scanner method, the surface is scanned by a flat-bed scanner. Then, the captured images are analyzed by different computer software. In this thesis, 22 concrete samples were examined by these two methods and the air void parameters were compared to those obtained from the standard method. Moreover, different parameters influencing the results of the test were examined and the precision of the results were compared to the recommendations of ASTM standard.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.405
Teacher spread0.369 · 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 designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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