MétaCan
Menu
Back to cohort

Comparison of Two Different Protocols for the Treatment of Acute Escherichia coli Mastitis in Dairy Cattle

2017· article· en· W2736878578 on OpenAlexvenueno aff
Vahideh Hamidi-Sofiani, Hossein Hamali, K. Nofouzi

Bibliographic record

VenueJournal of Buffalo Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
FundersUniversity of Tabriz
KeywordsCeftiofurMastitisMedicineAnimal sciencePlaceboGroup BAntibioticsVeterinary medicineIce calvingDairy cattleInternal medicineBiologyLactationMicrobiologyCephalosporinPregnancy

Abstract

fetched live from OpenAlex

E-coli mastitis is one of the most frequent causes of environmental mastitis in the dairy cattle worldwide. The purpose of this field study was to compare the efficacy of ceftiofur (HCL) in conjunction with supportive measures versus supportive measures alone for treatment of dairy cows affected with naturally occurring acute form of E. coli mastitis. From January 2014 to December 2016 a total number of 100 cows naturally affected by acute E-coli mastitis randomly were allocated into two groups. A milk sample from the affected quarter was collected for bacteriological tests on the first day of treatment. In group A (control), fifty cows received ceftiofur (HCL) 1mg/5kg/BW, flunixin meglumine 2.2mg/kg, calcium borogluconate 40%, 250ml and hypertonic saline (Nacl 7.2 %,) 5ml/kg. In group B (treatment, n=50), cows received the same drugs mentioned for group A, except ceftiofur (HCL) which replaced by placebo. In the group A, 41cows (82%) and in the group B, 2 cows (4%) were survived respectively. The rates of quarter health recovery in the groups A and B were 31.7% and 0% respectively. The differences between two groups were significant (P≤0.01). In conclusion our results indicated that treatment of cows affected with naturally occurring acute form of E. coli mastitis without application of effective antibiotic(s) such as ceftiofur (HCL) and fluid therapy almost impossible.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.259

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.109
GPT teacher head0.395
Teacher spread0.286 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Buffalo ScienceSame topicMilk Quality and Mastitis in Dairy CowsFrench-language works237,207