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Record W2111210158 · doi:10.1002/col.21972

Interference colorimetry of starch granules

2015· article· en· W2111210158 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

VenueColor Research & Application · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsChromaticityInterference (communication)ColorimetryOpticsDiagramChemistryMaterials scienceAnalytical Chemistry (journal)MathematicsPhysicsChromatographyComputer scienceChannel (broadcasting)StatisticsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Starch granules viewed under a polarizing microscope may exhibit vivid interference colors – how can they be measured? A tilting compensator was used to generate interference colors, they were measured by spectrophotometry (400–700 nm at 10 nm intervals), and the weighted ordinate method was used to calculate chromaticity coordinates. There was a reasonable correspondence between the subjective terms used to describe interference colors, and those used for the CIE diagram. Three different charts of interference colors were measured by fiber‐optics – only one was close to the interference colors of the tilting compensator ( r = 0.805 for CIE x , and r = 0.874 for CIE y , both P < 0.005). The spectra of various interference colors were like sine waves, whereas the matching spectra from charts were irregular with occasional peaks or dips. Thus, radically different spectra shared very similar chromaticity coordinates. As anticipated from first principles, the diameter of starch granules had a strong effect on their chromaticity coordinates (from r = 0.78 to r = 0.87, all P < 0.001). © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 352–357, 2016

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.312
GPT teacher head0.398
Teacher spread0.087 · 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