MétaCan
Menu
Back to cohort
Record W7135780630

Fluctuation of Earth's magnetic field and its influence on dogs

2016· dissertation· cs· W7135780630 on OpenAlexaboutno aff
Kateřina Beránková

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2016
Typedissertation
Languagecs
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsOrientation (vector space)Magnetic fieldCompassMagnetoreceptionLabrador RetrieverBreedField (mathematics)Demagnetizing field
DOInot available

Abstract

fetched live from OpenAlex

Fluctuation of Earth's magnetic field and its influence on dogs Kateřina Beránková The aim of the bachelor thesis was monitoring and documenting the orientation selected breeds of dogs when feeding, depending on fluctuation of the Earth's magnetic field. The theoretical part of this thesis deals with a summary of information about one of the three selected breeds of dogs (deutscher boxer), that was just like the rest of breeds used as a model animal for the practical part. In the next part is introduced magnetoreception, therefore, the ability of animals to perceive the Earth's magnetic field and its hypothetical models of functioning. There is also described magnetic orientation and its other forms which are magnetic map, magnetic compass and magnetic alignment, which is spontaneous orientation of the body axis of the animal in certain direction, for example, in the North-South axis by influence of the Earth's magnetic field. The practical part of the thesis mainly deals with exploring the influence of the Earth's magnetic field on the orientation of the head and of the body axis, when dogs are feeding. Selected breeds of dogs were Deutscher boxer, Bernese mountain dog, Chodsky dog and hybrid of Labrador retriever and Siberian husky. Statistical analysis showed North-South direction preference only in the case of the breed Chodsky dog. For other breeds of dogs, East-West orientation was dominated.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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 designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicHemispheric Asymmetry in NeuroscienceFrench-language works237,207