Claim · 2021-07-15 · publication · Stated in source · Supported

Highly accurate protein structure prediction with AlphaFold (2021) cites Deep Residual Learning for Image Recognition.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

Highly accurate protein structure prediction with AlphaFold (2021) → cites → Deep Residual Learning for Image Recognition

Where it appears

No collection page holds this claim. It is listed with its records in the explorer.

Claim and evidence

Highly accurate protein structure prediction with AlphaFold (2021)cites ↓Deep Residual Learning for Image Recognition

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2021-07-15 · publication Records dated 2021 →

Scope and limitsAn explicit reference only; neither agreement nor influence. The citing text does not identify which version of the work was read.

The evidence 01

primary sourceSupports the claim

Highly accurate protein structure prediction with AlphaFold

Nature · 2021-07-15

Archived copy, captured 2026-09-23: Highly accurate protein structure prediction with AlphaFold

Cite the original source

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Paraphrase

The text names the work by its title.

Location in source reference or mention by title

Machine-checked · 2026-10-31

Source details and check notes

Authors: John Jumper; Richard Evans; Alexander Pritzel; Tim Green; Michael Figurnov; Olaf Ronneberger; Kathryn Tunyasuvunakool; Russ Bates; Augustin Žídek; Anna Potapenko; Alex Bridgland; Clemens Meyer; Simon A. A. Kohl; Andrew J. Ballard; Andrew Cowie; Bernardino Romera-Paredes; Stanislav Nikolov; Rishub Jain; Jonas Adler; Trevor Back; Stig Petersen; David Reiman; Ellen Clancy; Michal Zielinski; Martin Steinegger; Michalina Pacholska; Tamas Berghammer; Sebastian Bodenstein; David Silver; Oriol Vinyals; Andrew W. Senior; Koray Kavukcuoglu; Pushmeet Kohli; Demis Hassabis
Version: Nature 596, 583–589 (2021), DOI 10.1038/s41586-021-03819-2; version of record HTML.
Canonical address: Open the canonical source ↗
Accessed: 2026-09-28
Language: English (en)
Archive copy: Open archived copy, captured 2026-09-23: Highly accurate protein structure prediction with AlphaFold. Captured 1896 days after the recorded publication date. An archive copy shows only what the archive retrieved on 2026-09-23. It does not prove what the page said earlier, and it can differ from the copy checked on 2026-09-28.
Attribution: John Jumper; Richard Evans; Alexander Pritzel; et al.. Highly accurate protein structure prediction with AlphaFold.
Reuse: No redistribution licence asserted.. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, key papers (research/key-papers). The citation was matched (title) in the text retrieved for the candidate pack on 2026-10-28 and re-found by its mechanical check. The paraphrase is Selekoa’s. A cross-family machine check (2026-10-30, item B070) found the citation in the citing text. No human editorial review.

Status and meaning

Editorial status. Not reviewed by an editor. An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.

Relation. An explicit reference to a work. Citation alone is neither agreement nor causal influence.

Date. Date of the citing source as recorded in the dataset; unknown where the dataset has none.

Record ID kp-cites-alphafold-paper-deep-residual-learning-image-recognition-2015