算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
cogpsych-tables-figures【设计与创意】Use when building tables and figures for a Cognitive Psychology (Elsevier) manuscript. Exhibits here carry the experiment-to-model-fit argument — they should overlay model predictions on data, show distributions and uncertainty, and report parameter estimates, not just bars of means. Designs exhibits; it does not run the analysis or fit the model.
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In Cognitive Psychology the central exhibit usually shows the model fitting the data — observed patterns with the model's predictions overlaid — because the contribution is the model, not the bare effect. Exhibits should reveal distributions and uncertainty, report parameter estimates with intervals, and let a reader judge model comparison at a glance. Bars of means hide exactly what this venue cares about.
For the recognition-memory program, the primary figure must show the fit, not the means.
Figure 1. Observed and model-predicted z-ROCs, Experiments 1-3.
Geometry: observed confidence-ROC points with 95% CIs, UVSD predicted
curve overlaid (solid) and DPSD predicted curve overlaid
(dashed) — the reader sees UVSD track the linear z-ROC.
Panels: one per experiment; shared axes for comparison.
Annotation: z-ROC slope 0.78 [0.72, 0.84]; dBIC = 14 favoring UVSD.
Note: defines the ROC metric, Ns, trials/bin, exclusion count, and
that bands are 95% intervals - readable without the main text.
Source: rendered by the deposited model-fitting script so values match.
Table 1. Model comparison: free parameters, -2logL, AIC, BIC, BF, by model.
| Exhibit | Home | Reason |
|---|---|---|
| Observed data + model fit (headline) | main text | this is the contribution |
| Model-comparison table (criteria + k) | main text | the comparison must be checkable |
| Parameter-recovery / model-recovery plots | supplement | needed for credibility, not the headline |
| Full per-subject fits | supplement | costs space, secondary to the group story |
| Stimulus lists / counterbalancing tables | supplement / materials deposit | provenance, not narrative |
Generate exhibits from the fitted result, not by retyping numbers (the usual source of
body-vs-supplement drift). Full map: execution-with-mcp. Cognitive Psychology is experimental — within-subject designs and mixed models dominate; report the model, the effect size, and multiple-comparison control.
etable (multi-model columns) or did_summary_to_latex straight from the
result_id.plot_from_result / enhanced_event_study_plot / event_study_table —
axis units and the SE/clustering note baked in.See a full fitted-result → exhibit chain in the JF execution walkthrough.
【Main exhibit】observed data + model fit (and rival)? [Y/N]
【Shows distribution + uncertainty + parameter intervals?】[Y/N]
【Model-comparison table】criteria + free-parameter counts? [Y/N]
【Self-contained + accessible?】notes, Ns, trials, grayscale/colorblind-safe? [Y/N]
【Reproducible?】matches deposited model script? [Y/N]
【Next】cogpsych-writing-style
../../resources/external_tools.md — plotting tools, model-fit visualization, recovery plots../../resources/official-source-map.md — exhibit and house-style expectations