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Record W7024055121

Reakce palearktických a nearktických sýkor na sympatrické a alopatrické predátory v krmítkových experimentech: existují regionální rozdíly v rozpoznávání predátorů a hodnocení jejich nebezpečnosti?

2014· dissertation· en· W7024055121 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2014
Typedissertation
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsKestrelSympatric speciationAllopatric speciationDoveStreptopeliaPredationSympatry
DOInot available

Abstract

fetched live from OpenAlex

We have examined wild palearctic and nearctic parids in their ability to recognize and assess a threat level of sympatric and allopatric predators. The study was conducted in Prague, Czech republic, on great tits (Parus major) and blue tits (Parus caeruleus) during the winter of 2013, and the following year in the city of Calgary, Canada, on black-capped chickadees (Poecile atricapillus). Three species of falcons (merlin (Falco columbarius), common kestrel (Falco tinnunculus) and american kestrel (Falco sparverius)), were chosen, two of which were sympatric and one was allopatric to the studied parid species in each area. We have also tested their reaction to nest predators magpies (eurasian magpie (Pica pica), black-billed magpie (Pica hudsonia)). Using two ground feeders in the winter time, we gave parids a choice between a feeder with either one of the three dummies of falcons, or a magpie, and a feeder with a dummy of either a hawk (the most dangerous predator of small birds) or a dove (a harmless bird of the same size as falcons). As a control we have only used sympatric species: eurasian sparrowhawk (Accipiter nisus), Cooper's hawk (Acipiter cooperii), eurasian collared dove (Streptopelia decaocto) and mourning dove (Zenaida macroura). Results from the city of Calgary did not produce any...

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0020.002
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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicAvian ecology and behaviorFrench-language works237,207