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Record W7100768495

Supplemental Experimental Procedures Physiological Preparation and Functional Imaging of Retinotopic Maps

2013· article· en· W7100768495 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsLidocaineCraniotomySalineHemostatLens (geology)
DOInot available

Abstract

fetched live from OpenAlex

To image mouse cortical retinotopy maps, we followed the method developed by Kalatsky and Stryker (2003). Adult mice were anesthetized with an intraperitoneal injection of urethane (1.0 g/kg in 10 % saline solution) supplemented by chlorprothixene (0.2 mg/mouse i.m.). In addition, lidocaine (2 % xylocaine jelly) was applied locally to all incisions. Atropine (5 mg/kg mouse) and dexamethasone (0.2 mg/mouse) were injected subcutaneously. The animals were placed in a stereotaxic apparatus, their temperature was maintained at 37.5°C, and electrocardiograph leads were attached to monitor the heart rate continuously throughout the experiment. A tracheotomy was performed in some experiments. A craniotomy was made over the visual area of the left hemisphere; the dura mater was left intact. Low-melting point agarose (3 % in saline) and a glass coverslip were placed over the exposed area. All experimental procedures were approved by the UCSF Committee on Animal Research. Optical images of the cortical intrinsic signal were obtained using a Dalsa 1M30 CCD camera (Dalsa, Waterloo, Canada) controlled by custom software. Using different tandem lens configurations (Nikon, Inc., Melville, NY), “medium-resolution ” (85 × 50 mm lenses, 7.2 × 7.2 mm image area) and “high-resolution ” (135 × 50 mm lenses, 4.6 × 4.6 mm image area) images

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)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.248
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2013
Admission routes1
Has abstractyes

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