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Record W6981779350

Faktory ovlivňující výběr boxu dojnicemi českého strakatého plemene skotu

2013· dissertation· en· W6981779350 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMilkingPreferenceAutomatic milkingStatistical analysisQuarter (Canadian coin)Preference test
DOInot available

Abstract

fetched live from OpenAlex

The objective of the dissertation thesis was to analyse factors affecting preference of cubicle of Czech Fleckvieh dairy cows. Monitoring was carried in farm GenAgro Ricany a. s., a period of 12 months (June 2011 -- May 2012). The objective of monitoring was one section - one quarter of stable (n = 98 cows). Total of 47 040 observations were analysed. Statistical evaluation of data was performed by STATISTICA 10.0. In the sectionwas comprised of 103 comfortable stalls (cubicles) distributed into 3 rows.. Row A -- closest to feeding table (32 cubicles); row B -- in the midle section (33 cubicles); row C -- close to the side wall (38 cubicles). In all factors (number and stage of lactation, milk yield, number of arrival from milking parlour, temperature and humidity in stable and THI, height in the cross) was found significantly influence (p < 0,01) on preference of cubicle row. In evaluation of preference of boxes it was found out, that the lowest occupation rate in whole observing was in those boxes, which are on the edge of rows. Also lower amount of visits was noted in boxes, which are surrounded from more than one side by wooden partition separating space for lying (box) from waterhole. On the contrary mostly occupied boxes were those, which are located in the middle of box rows. Further higher preference rate of left side when lying was found in all observed influences, identically at both outer rows. On the contrary dairy cows preferred right side when lying in middle row.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.270
Teacher spread0.258 · 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.

Study designNot applicable
Domainnot available
GenreOther

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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