{
  "certificate": {
    "id": "2026-019",
    "title": "CODECHECK Certificate 2026-019",
    "url": "https://codecheck.org.uk/register/certs/2026-019/",
    "wikidata": "Q141269763"
  },
  "paper": {
    "title": "Photoreceptor-specific scene statistics reveal melanopic structure in natural environments",
    "authors": [
      {
        "name": "Niloufar Tabandeh",
        "orcid": "0000-0002-7971-8589"
      },
      {
        "name": "Manuel Spitschan",
        "orcid": "0000-0002-8572-9268"
      }
    ],
    "reference": "https://doi.org/10.1016/j.isci.2026.116661",
    "abstract": {
      "text": "Natural scenes shape visual perception and non-visual responses, yet the melanopsin pathway, the retina's key circadian input, is rarely quantified in this context. We measured spectral and spatial properties of 671 natural scenes: indoor scenes without windows ( n = 115), indoor scenes with windows ( n = 194), and outdoor scenes ( n = 362), across all five human photoreceptors. Radiance and photometric metrics increased systematically from windowless indoor view (mean melanopic EDI 280 lx) to indoor scenes with window view (2386 lx) to outdoor scenes (12,142 lx), with melanopic and photopic illuminance strongly correlated ( r > 0.98, p < 10 −5 ). Beyond overall α -opic exposure, melanopic input exhibited structured spatial variation. The image-level root-mean-square (RMS) contrast ranged from 0.001 to 0.365 across categories (lowest in indoor scenes and highest outdoors), and correlated with melanopic luminance indoors with windows (r = 0.495) and outdoors (r = 0.477) but not windowless scenes (r = 0.026). Melanopic amplitude spectra followed 1/ f -like power laws, steeper slopes indoors (modal ≈ − 1.4 ) and flatter outdoors (modal ≈ − 1.1 ), revealing photoreceptor-resolved regularities in natural melanopic input.",
      "source": "OpenAlex"
    },
    "openalex": "https://openalex.org/W4416186252",
    "wikidata": "Q141269482"
  },
  "codecheck": {
    "codecheckers": [
      {
        "name": "Jan Haacker",
        "orcid": "0000-0002-5464-2442"
      }
    ],
    "check_time": "2026-07-07T14:00:00",
    "repository": "github::codecheckers/certificate-2026-019",
    "report": "https://doi.org/10.5281/zenodo.21238767",
    "type": "community",
    "venue": "codecheck",
    "summary": "The checked repository includes code to reproduce all figures shown in\nthe associated manuscript titled \"Photoreceptor-specific scene\nstatistics reveal melanopic structure in natural environments\"\nincluding one supplementary figure. The workflow is instructed by a\ndetailed recipe in the file `README.md` and structured into three main\nparts and small alignment steps. The main parts are downloading the\ninput data and running two notebooks consecutively. Following the\ninstructions successfully produces the manuscript and supplement\nfigures; however, in Figures 1 to 4 structural changes can occur,\nprobably due to a non-deterministic order when processing input files.\nThe code is entirely written in Python allowing to understand the\nmechanics by reading and uses a transparent repository structure.\n",
    "manifest": [
      {
        "file": "results/tables/merged_wp_jeti_metadata_df.csv",
        "comment": "Merged WP, JETI, and metadata"
      },
      {
        "file": "results/tables/average_pixels_correlation_df.csv",
        "comment": "Pixel-level alpha-opic correlations"
      },
      {
        "file": "results/tables/amplitude_spectra_regression_view_df.csv",
        "comment": "Amplitude spectra regressions by view"
      },
      {
        "file": "results/tables/jeti_statistics_overall.csv",
        "comment": "Overall JETI central statistics"
      },
      {
        "file": "results/tables/jeti_statistics_per_view.csv",
        "comment": "JETI central statistics by view"
      },
      {
        "file": "results/tables/wp_statistics_overall.csv",
        "comment": "Overall WP central statistics"
      },
      {
        "file": "results/tables/wp_statistics_per_view.csv",
        "comment": "WP central statistics by view"
      },
      {
        "file": "results/tables/overexposed_percentage_per_view.csv",
        "comment": "Overexposed pixels by view"
      },
      {
        "file": "results/figures/broken_bar_plot_mEDI_logscale_location.png",
        "comment": "Figure 1 component, mEDI by location"
      },
      {
        "file": "results/figures/Overexposed_pixels_per_view.png",
        "comment": "Figure 1 component, overexposed pixels"
      },
      {
        "file": "results/figures/Figure1.png",
        "comment": "Figure 1"
      },
      {
        "file": "results/figures/Figure1.pdf",
        "comment": "Figure 1"
      },
      {
        "file": "results/figures/MelEDI_vr_illuminance_logscale_KDE_jeti.png",
        "comment": "Figure 2 component, melanopic EDI vs illuminance"
      },
      {
        "file": "results/figures/Wp_vr_jeti_KDE_logscale.png",
        "comment": "Figure 2 component, WP vs JETI"
      },
      {
        "file": "results/figures/Correlation_matrix_α-opics_radiance_per_view.png",
        "comment": "Figure 2 component, JETI alpha-opic correlations"
      },
      {
        "file": "results/figures/Figure2.png",
        "comment": "Figure 2"
      },
      {
        "file": "results/figures/Figure2.pdf",
        "comment": "Figure 2"
      },
      {
        "file": "results/figures/Correlation_matrix_α-opics_average_radiances_per_view.png",
        "comment": "Figure 3 component, average radiance correlations"
      },
      {
        "file": "results/figures/Correlation_matrix_α-opics_pixel_by_pixel_per_view.png",
        "comment": "Figure 3 component, pixel-level correlations"
      },
      {
        "file": "results/figures/Figure3.png",
        "comment": "Figure 3"
      },
      {
        "file": "results/figures/Figure3.pdf",
        "comment": "Figure 3"
      },
      {
        "file": "results/figures/Violin_plot_rms_contrast_per_view_flip.png",
        "comment": "Figure 4 component, RMS contrast by view"
      },
      {
        "file": "results/figures/RMS_vr_luminance_KDE_logscale_WP.png",
        "comment": "Figure 4 component, RMS contrast vs luminance"
      },
      {
        "file": "results/figures/Figure4.png",
        "comment": "Figure 4"
      },
      {
        "file": "results/figures/Figure4.pdf",
        "comment": "Figure 4"
      },
      {
        "file": "results/figures/Figure5.png",
        "comment": "Figure 5"
      },
      {
        "file": "results/figures/Figure5.pdf",
        "comment": "Figure 5"
      },
      {
        "file": "results/figures/Min_slope.png",
        "comment": "Figure 6 component, low-slope example"
      },
      {
        "file": "results/figures/Max_slope.png",
        "comment": "Figure 6 component, high-slope example"
      },
      {
        "file": "results/figures/Figure6.png",
        "comment": "Figure 6"
      },
      {
        "file": "results/figures/Figure6.pdf",
        "comment": "Figure 6"
      },
      {
        "file": "results/figures/Figure7.png",
        "comment": "Figure 7"
      },
      {
        "file": "results/figures/Figure7.pdf",
        "comment": "Figure 7"
      },
      {
        "file": "results/figures/Figure_Sup.png",
        "comment": "Supplementary figure"
      },
      {
        "file": "results/figures/Figure_sup.pdf",
        "comment": "Supplementary figure"
      }
    ]
  }
}