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Record W4394299669 · doi:10.6084/m9.figshare.7941665

Microglia and neurons in the hippocampus of migratory sandpipers

2019· dataset· en· W4394299669 on OpenAlexaboutno aff
Cristovam Guerreiro Diniz, Nara Gyzely de Morais Magalhães, Aline Andrade de Sousa, Carlos Santos Filho, Daniel Guerreiro Diniz, Camila Mendes de Lima, Dario Carvalho Paulo, Patrick Douglas Côrrea Pereira, David F. Sherry, Cristovam Wanderley Picanço Diniz

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsHippocampusMicrogliaNeuroscienceGeographyBiologyImmunologyInflammation

Abstract

fetched live from OpenAlex

The semipalmated sandpiper Calidris pusilla and the spotted sandpiper Actitis macularia are long- and short-distance migrants, respectively. C. pusilla breeds in the sub-arctic and mid-arctic tundra of Canada and Alaska and winters on the north and east coasts of South America. A. macularia breeds in a broad distribution across most of North America from the treeline to the southern United States. It winters in the southern United States, and Central and South America. The autumn migration route of C. pusilla includes a non-stop flight over the Atlantic Ocean, whereas autumn route of A. macularia is largely over land. Because of this difference in their migratory paths and the visuo-spatial recognition tasks involved, we hypothesized that hippocampal volume and neuronal and glial numbers would differ between these two species. A. macularia did not differ from C. pusilla in the total number of hippocampal neurons, but the species had a larger hippocampal formation and more hippocampal microglia. It remains to be investigated whether these differences indicate interspecies differences or neural specializations associated with different strategies of orientation and navigation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.059
GPT teacher head0.276
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueFigshare→Same topicNeuroinflammation and Neurodegeneration Mechanisms→French-language works237,207→