Supplemental Experimental Procedures Physiological Preparation and Functional Imaging of Retinotopic Maps
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.140 | 0.039 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".