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Record W6921570734 · doi:10.7281/t1/thlc8n

Data and software associated with the publication: Control and recalibration of path integration in place cells using optic flow

2024· dataset· en· W6921570734 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Data Repository, Duke University · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsBritish Columbia Centre of Excellence for Women's Health
FundersAssociation for Research in OtolaryngologyU.S. Public Health Service
KeywordsPath integrationPath (computing)SoftwareCode (set theory)Flow (mathematics)Control (management)Time delay and integrationControl softwareScheme (mathematics)

Abstract

fetched live from OpenAlex

This repository includes the dataset and code used in the study of the influence of optic flow on rodent hippocampal place cells and in recalibrating the path integrator. The dataset contains post-processed CA1 place cell electrophysiology data, animal behavior data, and experiment control and sensor data recorded from 5 Long-Evans rats as they ran laps in the Dome VR apparatus. The experiment manipulation is described in the publication "Control and recalibration of path integration in place cells using optic flow”.

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.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0030.003
Research integrity0.0000.001
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 head0.078
GPT teacher head0.316
Teacher spread0.239 · 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