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🚩 Minted in Nanopublication

The HEALPix-NESTED substrate makes sphere-aware ML latitude-invariant, discipline-transferable, and ... Research-Synthesis comment... approve/disapprove... edit as derived nanopublication... create new with same template...

This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

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This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

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Q1507383

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spherical-ml-substrate-synthesis-2026

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spherical-ml-substrate-synthesis-2026

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spherical-ml-substrate-synthesis-2026

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Q5629401

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spherical-ml-substrate-synthesis-2026

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spherical-ml-substrate-synthesis-2026

http://www.w3.org/2000/01/rdf-schema#label has the label (this is a literal)

"The HEALPix-NESTED substrate makes sphere-aware ML latitude-invariant, discipline-transferable, and biodiversity-attribution-ready"

This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

https://w3id.org/sciencelive/o/terms/hasSynthesisDescription has the synthesis conclusion (this is a literal)

"Three independent tests on the HEALPix-NESTED substrate jointly establish that sphere-aware operators recover detection accuracy lat-lon flat operators lose, transfer across discipline pairs without retraining, and integrate with marine biodiversity occurrence data on a single shared substrate — without re-projection at any step. The within-discipline test (chain A, notebook 04) shows the lat-lon-flat matched filter collapsing from 1.000 to 0.500 chance at 70–80° latitude while the sphere-harmonic band-pass matched filter holds at 1.000 across all four test bands. The cross-discipline test (chain C, notebook 06) shows the same sphere-aware pipeline transferring at 1.000 from a cosmology-like training domain to a climate-like test domain without retraining, while the flat baseline drops to 0.845 on the same transfer. The real-data test (chain B, notebook 05) shows that when the climate-event field and the biodiversity occurrence field meet on the same HEALPix substrate, 94.0 percent of 765 marine GBIF records during the documented 2011 Ningaloo Niño event sat on cells that experienced marine-heatwave conditions in the same window Wernberg et al. 2016 documented the kelp regime shift in. The shared property — that sphere-harmonic convolution is exactly rotation-equivariant on the sphere, while lat-lon convolution is only translation-equivariant in pixel space — is what makes the substrate the right common DGGS for Copernicus EO, Destination Earth climate models, and biodiversity-impact attribution to interoperate."

This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

https://w3id.org/sciencelive/o/terms/hasRecommendationDescription has the recommendation (this is a literal)

"(1) When training ML detection or classification models on globally-distributed Earth-observation, climate, or biodiversity data, render features on a HEALPix-NESTED substrate (spherical for cosmology / synthetic experiments, WGS84-ellipsoidal via healpix-geo for geoscience) before applying convolutions; the substrate choice is what separates "works at the equator only" from "works at every latitude". (2) When integrating biodiversity occurrence data with Copernicus Marine SST, NOAA OISST, ERA5, or DestinE climate-model output for impact-attribution work, co-locate all four sources on a shared HEALPix-NESTED grid (NESTED ordering for hierarchical bit-shift refinement) at the resolution that matches the coarsest input, then perform overlap statistics there; do not perform per-source lat-lon aggregation followed by raster-level joins. (3) When evaluating sphere-aware versus flat ML pipelines, report accuracy at multiple test latitude bands and on at least one cross-discipline transfer regime; in-distribution-only metrics under-state the substrate effect. (4) Investments in sphere-aware models from one discipline (cosmology DeepSphere, foscat scattering networks, DLWP-HEALPix global weather forecasting) carry directly over to the other disciplines on the same HEALPix substrate; budget integration work as a feature-extractor port rather than a from-scratch retrain."

This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

https://w3id.org/sciencelive/o/terms/hasConditionsDescription has the conditions (this is a literal)

"Scope: global ML detection / classification tasks where features can be expressed on a HEALPix-NESTED grid, including but not limited to sea-surface-temperature anomaly fields (NOAA OISST v2.1, Copernicus Marine SST, ERA5), tropospheric or stratospheric atmospheric fields (DLWP-HEALPix forecast outputs, ClimateNet), marine biodiversity occurrences (GBIF, OBIS) at coarsest-feature resolution, and synthetic Gaussian-random-field samples with compact features. Methods: sphere-harmonic transforms via healpy.map2alm / alm2map, sphere-harmonic-domain convolutions via aₗₘ → aₗₘ · fₗ · bₗ, equal-area cell aggregation via numpy.bincount on healpy.ang2pix(..., nest=True). Domains: cosmology, climate, Earth observation, marine biodiversity, atmospheric science. The latitude-invariance and cross-discipline-transfer claims hold for any compact-feature detection task at fixed angular scale on the HEALPix substrate; the biodiversity-attribution claim is documented for the 2011 Ningaloo Niño event in the Western Australian region but the substrate-and-method combination generalises to any documented MHW or atmospheric-event case with available occurrence data."

This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

https://w3id.org/sciencelive/o/terms/hasLimitationsDescription has the limitations (this is a literal)

"(1) The within-discipline and cross-discipline tests use synthetic data with controlled feature physics; the substrate-dependence is demonstrated via a minimal (max, mean, std) matched-filter feature triple to isolate the substrate effect from the model class, not via a deep learned representation. The numerical magnitudes (1.000 vs 0.500, 1.000 vs 0.845) reflect the geometric mechanism cleanly but are upper bounds on what richer learned representations like DeepSphere graph CNNs or foscat scattering networks would deliver on real data. (2) The real-data biodiversity-attribution case (chain B) uses a 3-year-baseline (2008–2010) simplification of the canonical Hobday et al. 2016 30-year 1991–2020 climatology and a fixed +1.5 °C anomaly threshold rather than the per-day-of-year 90th-percentile threshold; the qualitative spatial footprint matches the documented Ningaloo Niño but the per-cell MHW-day count is approximate. (3) The biodiversity-overlap statistic is exposure-only (records on MHW cells), not a causal attribution of biodiversity change to MHW conditions; the linkage to Wernberg et al. 2016 kelp regime shift is via spatial-temporal coincidence with the documented event. (4) The cross-discipline transfer test uses synthetic discipline regimes constructed to share feature physics across different background spectra; true cross-discipline transfer from real cosmology data (e.g., Planck CMB on HEALPix) to real climate data (e.g., DLWP-HEALPix forecasts on HEALPix) would require integrating with foscat or DeepSphere as future work. (5) All HEALPix work in this synthesis uses NESTED ordering throughout per the project-wide convention; results for RING-ordered HEALPix at the same resolution are expected to be equivalent but were not separately tested."

This is a local identifier minted within the nanopublication. https://w3id.org/sciencelive/n...al-ml-substrate-synthesis-2026

spherical-ml-substrate-synthesis-2026

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spherical-ml-substrate-synthesis-2026

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spherical-ml-substrate-synthesis-2026

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"2026-05-07"

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https://orcid.org/0000-0002-1784-2920

Anne Fouilloux

https://orcid.org/0000-0002-1784-2920

Anne Fouilloux

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"Anne Fouilloux"

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"The HEALPix-NESTED substrate makes sphere-aware ML latitude-invariant, discipline-transferable, and biodiversity-attribution-ready"

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"2026-05-08T20:21:07.483Z"

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RApmrqOEr4

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spherical-ml-substrate-synthesis-2026

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sig

http://purl.org/nanopub/x/hasSignatureTarget has as target This is the identifier for this whole nanopublication. https://w3id.org/sciencelive/np/RA6r8sefdZ... this nanopublication .

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"RSA"

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sig

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sig

http://purl.org/nanopub/x/signedBy is signed by https://orcid.org/0000-0002-1784-2920

Anne Fouilloux

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http://purl.org/dc/terms/creator

creator

https://orcid.org/0000-0002-1784-2920

Anne Fouilloux

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https://creativecommons.org/licenses/by/4.0/

4.0

Anne Fouilloux, 8 May 2026, 20:21:07 UTC

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