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Record W4392787057 · doi:10.1055/a-2219-9154

Selektives antibiotisches Trockenstellen bei Milchkühen in Rheinland-Pfalz, dem Saarland und Hessen – eine Umfrage unter Landwirten

2024· article· de· W4392787057 on OpenAlex
Theresa Scheu, F. Reinecke, Lisa Münnich, Amely Campe

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTierärztliche Praxis Ausgabe G Großtiere / Nutztiere · 2024
Typearticle
Languagede
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
Fundersnot available
KeywordsHerdMastitisQuarter (Canadian coin)Somatic cell countAgricultural scienceMedicineVeterinary medicineAnimal scienceGeographyToxicologyBiologyLactationIce calving

Abstract

fetched live from OpenAlex

OBJECTIVE: With the Regulation (EC) 6/2019, antibiotic drying off of the entire dairy herd is no longer permissible. Hence, it is necessary to establish selective antibiotic drying off (SDCT: Selective Dry Cow Therapy) in dairy herds. With the publication of the PraeRi study in 2020, systematic data for the implementation of SDCT on farms became available for several German states. For Rhineland-Palatinate, Saarland and Hesse this type of information is only available from individual projects. Therefore, the aim of this survey was to increase the knowledge concerning the implementation of SDCT in dairy farms located in these states. MATERIAL AND METHODS: An online questionnaire was sent via newsletters to farmers and was published in the regional farmers' bulletins in the described catchment area. The questionnaire inquired about the saving of antibiotics during drying off, the criteria guiding the farmer's decision (cell count from monthly dairy herd improvement data (DHI), mastitis history, microbiological examination of quarter foremilk samples, California mastitis test), use of teat sealants and the type of dry off procedure (abrupt/gradual). RESULTS: A total of 103 questionnaires were evaluated, making the response rate ~1% for Hesse, ~3% for Saarland, and ~5% for Rhineland-Palatinate based on the number of included farms. Approximately 29% of the farmers dried off one out of four cows, 20% half, 23% three out of four and 13% all cows without using antibiotics. Eighty-nine farm managers based their decision on the somatic cell counts of DHI. Additional criteria influencing the decision were the mastitis history, results of the California Mastitis Test, or a combination of both. In 76 farms cows were dried off abruptly. In 79 farms teat sealers were used. CONCLUSIONS: Application of SDCT is established in most of the farms that participated in the survey, even though the proportion varied between farms. Legal requirements are not the only reason farmers need to increasingly deal with SDCT; sustainability programs of the dairies rely on selective drying off as well. Herd veterinarians should be supportive in implementing these measures to achieve good udder health while reducing the use of antimicrobials to a necessary minimum.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.019
GPT teacher head0.270
Teacher spread0.251 · 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