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Record W2069235541 · doi:10.1080/00218460490477684

AXISYMMETRIC DROP SHAPE ANALYSIS (ADSA) FOR THE DETERMINATION OF SURFACE TENSION AND CONTACT ANGLE

2004· article· en· W2069235541 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

VenueThe Journal of Adhesion · 2004
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRotational symmetrySurface tensionDrop (telecommunication)Contact angleMechanicsFinite element methodMaterials sciencePhysicsMechanical engineeringComposite materialEngineeringThermodynamics

Abstract

fetched live from OpenAlex

A drop shape analysis technique called Axisymmetric Drop Shape Analysis (ADSA) has been developed in our laboratory over the last twenty years. ADSA is a powerful technique for the measurement of interfacial tensions and contact angles of pendant drops, sessile drops, and bubbles. In essence, it relies on the best fit between theoretical Laplacian curves and an experimental profile. Despite the general success of ADSA, deficient results may be obtained for drops close to spherical shape. Since the sources of these limitations were unknown, the entire ADSA technique, including hardware and software, has been reviewed. The key element of the new generation of ADSA is the modularization of the software, because a firm fixed package would not be suitable for all experimental situations. Another novel feature of the methodology is the development of a quantitative criterion, i.e., a shape factor, that determines the range of drop shapes, in which ADSA succeeds or fails.

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)0.002
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 score0.151
Threshold uncertainty score0.154

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.030
GPT teacher head0.274
Teacher spread0.244 · 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