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A Quarter Individual Milking Machine “Stimulactor®” in a Camel Farm in Switzerland: According to Field Study

2023· article· en· W4390231516 on OpenAlexaboutno aff
Shehadeh Kaskous

Bibliographic record

VenueJournal of Camel Practice and Research · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Diversity and Health Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)MilkingVeterinary medicineField (mathematics)BiologyAgricultural scienceAnimal scienceGeographyMedicineMathematicsArchaeology

Abstract

fetched live from OpenAlex

The aim of the field study was to test the performance of the quarter-individual milking machine “StimuLactor” (ST-C) in a camel farm in Switzerland. Eight one-humped lactating dromedaries were used for this purpose. The camels were milked twice a day with a unit milking machine-StimuLactor for camels. The setting of the milking machine was as follows: vacuum level 36 kPa, pulsation rate 90 cycles/min and, pulsation ratio 65/35. In addition, the milking machine was equipped with sequential pulsation (25% offset quarter to quarter) and the teat cups are equipped with round silicone liners and an air inlet valve (Bio-Milker). Daily milk yield was recorded over a period of one year and milk samples were taken for qualitative analysis. The results have shown that after using the new milking machine no pathogenic bacteria were detected in the milk produced during the trial period. The examined milk parameters fat, protein, lactose, somatic cell count (SCC) and non-pathogenic bacteria (NPB) were in the physiological range and the concentration were 3.33%, 2,39%, 4.09%, 79000 cells/ml and 6150 b/ml, respectively. Finally, milking with StimuLactor has shown very good results, since this milking machine has been adapted to the anatomical, morphological and physiological characteristics of the camel’s udder.

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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.148
GPT teacher head0.433
Teacher spread0.285 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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