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Record W3148147257 · doi:10.1101/pdb.prot106831

Bulk Dye Loading for In Vivo Calcium Imaging of Visual Responses in Populations of <i>Xenopus</i> Tectal Neurons

2021· article· en· W3148147257 on OpenAlexaff
Peter William Hogg, Kurt Haas

Bibliographic record

VenueCold Spring Harbor Protocols · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
Fundersnot available
KeywordsXenopusCalcium imagingTectumReceptive fieldNeuroscienceIn vivoTwo-photon excitation microscopyTadpole (physics)BiologyBiophysicsChemistryCalciumMidbrainOpticsPhysicsFluorescenceCentral nervous system

Abstract

fetched live from OpenAlex

Bulk loading of neurons with fluorescent calcium indicators in transparent albino Xenopus tadpoles offers a rapid and easy method for tracking sensory-evoked activity in large numbers of neurons within an awake developing brain circuit. In vivo two-photon time-lapse imaging of an image plane through the optic tectum allows defining receptive field properties from visual-evoked responses for studies of single-neuron and network-level encoding and plasticity. Here, we describe loading the Xenopus tadpole optic tectum with the membrane-permeable AM ester of Oregon Green 488 BAPTA-1 (OGB-1 AM) for in vivo imaging experiments.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.099
GPT teacher head0.418
Teacher spread0.319 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations2
Published2021
Admission routes1
Has abstractyes

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