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Record W183193011

A method of testing the quality of milk using optical capillaries

2009· article· en· W183193011 on OpenAlex
M. Borecki, Maciej Szmidt, Michał Korwin Pawłowski, Maria Bebłowska, Tomasz Niemiec, Paweł Wrzosek

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

VenuePhotonics Letters of Poland · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsSomatic cell countBulk tankMastitisQuality (philosophy)California mastitis testPlate countRaw milkMathematicsFood sciencePhysicsBiologyHerdBacteriaAnimal scienceMicrobiologyLactation
DOInot available

Abstract

fetched live from OpenAlex

The milk quality is determined by its visual appearance, absence of adulterating substances and ability to meet specific quality standards for somatic cell count (SCC), and bacteria count. There exist several diagnostic tests of milk quality. Some of them are applicable on dairy farms, like, for example, the California Mastitis Test (CMT) and the Milk Conductivity Test (MCT). Other tests, such as the bulk milk bacterial count, the bulk tank somatic cell count and tests for adulterants like water, sediments or antibiotics, are used in laboratories. The knowledge required to successfully apply the existing milk quality tests can be rather extensive and pertains both to the methodology and the diagnostic capabilities of a given test. Therefore, there is a need for new simple and low-cost methods of milk quality testing. This paper presents a new method of milk quality classification using low-cost optical capillaries. In this method, milk quality is determined by observation of milk behaviour under specific heating conditions using a simple low-cost photonic system with optical capillaries. We show that the optical capillary is a suitable tool for analysing liquids showing high scattering of light, such as milk. Full Text: PDF References: El-Rashidy A.A., Fox L.K., Gay J.M.,Diagnosis of Staphylococcus aureus intramammary infection by detection of specific antibody titer in milk, J. Dairy Sci., vol. 75, pp. 1430-1435, 1992. [CrossRef] Reinemann D.J., Mein G.A., Bray D.R., et al.,Troubleshooting high bacteria counts in farm milk, Univ. Wisconsin Coop Ext Pub A3705, Madison WI, 1999. Karlsson A.O., Ipsen R., Ardo Y.,Relationship between physical properties of casein micelles and rheology of skim milk concentrate, J. Dairy Sci. Vol. 80 pp. 3784-3797, 2005. [CrossRef] McMahon D.J., Brown R.J., Composition, structure and integrity of casein micelles: a review, J. Dairy Sci, vol. 67, pp. 499-512, 1984. [CrossRef] Dress P., Belz M., Klein K.F., Grattan K.T.V., Franke H.,Water-core-waveguide for pollution measurements in the deep ultra-violet, Applied Optics, vol. 37, pp. 4991-4997, 1998. [CrossRef] Romaniuk R., Dorosz J.,Technology of soft-glass optical fiber capillaries, Proc. of SPIE, vol. 6347, pp. 634710, 2006. [CrossRef] Borecki M, Korwin Pawlowski M., Wrzosek P., Szmidt J.,Capillaries as the components of photonic sensor micro-systems, J. of MS&T, vol. 19, pp. 065202, 2008. Borecki M.,Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle, Sensors, vol. 7, pp. 384-399, 2007. [CrossRef]

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.253

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)0.0000.000

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 head0.098
GPT teacher head0.323
Teacher spread0.226 · 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