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Record W6946415458 · doi:10.34657/171

Anwendung der Infrarotthermografie bei ferkelführenden Sauen

2013· article· de· W6946415458 on OpenAlexaboutno aff

Bibliographic record

VenueTIB Repositorium · 2013
Typearticle
Languagede
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsLabrador RetrieverStatistical analysisContext (archaeology)Postpartum period

Abstract

fetched live from OpenAlex

In der Nutztierpraxis gilt die Rektaltemperatur als einer der wichtigsten Indikatoren für die Tiergesundheit. Die rektale Temperaturmessung ist jedoch zeitaufwendig und erfordert direkten Tierkontakt. Die Infrarotthermografie (IR-Thermografie) stellt hingegen eine nichtinvasive, kontaktlose Methode dar, um die Körpertemperatur zu messen. Ein Versuch an Sauen im Abferkelbereich unter Praxisbedingungen hat gezeigt, dass sich die Körperregionen Auge und Ohrrücken zur Erfassung der Körpertemperatur mittels IR-Thermografie gut eignen. Damit kann die IR-Thermografie einen wesentlichen Beitrag zur gezielten Krankheitsprävention und zur Verbesserung des Tierwohls ferkeIführender Sauen leisten.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.018

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 head0.004
GPT teacher head0.183
Teacher spread0.179 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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