In 41.3 million natural-science papers (1980–2025), researchers who used AI as a research method published 3.02 times as many papers a year, received 4.84 times as many citations and became research project leaders 1.37 years sooner than researchers who did not.

SocioLens project,

Claim LD09-SL-C01 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: strong scope
Verification state: Checked against the primary source. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: A causal effect of adopting AI, a within-person change, or any statement about the social sciences or about chat assistants
Limitations: The authors state they “cannot fully identify the causal linkage between AI adoption and scientific impact”; adopters and non-adopters differ in ways the comparison does not remove; a matched-cohort check in the preprint’s supplement (arXiv version 4; the journal supplement was not read) reports much smaller gaps by career year 10 (24.45% more citations, 9.61% more output); the first preprint version reported different headline numbers
Source (as cited): Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026
Source type: Peer-reviewed journal article (recorded as “Peer-reviewed journal article”)
Institutional position: Independent academic (Tsinghua University, University of Chicago, Zhongguancun Academy and Santa Fe Institute)
Maturity of the evidence: Emerging evidence
Recorded date: 15 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026 (Peer-reviewed journal article)
Read the original

Version

This is the current version, v1.0. Earlier versions stay available, and their records never change.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): ESTIMATE (as printed: “ESTIMATE”)
Publication status (coded): ELIGIBLE (STRONG_SCOPE) (as printed: “ELIGIBLE WITH STRONG SCOPE QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): PEER_REVIEWED_JOURNAL_ARTICLE
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD09-SL-C01	—
2	PUBLIC-FACING CLAIM	In 41.3 million natural-science papers (1980–2025), researchers who used AI as a research method published 3.02 times as many papers a year, received 4.84 times as many citations and became research project leaders 1.37 years sooner than researchers who did not.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	A — Science and scholarship	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026	source_ids: SRC-SL-HAO-XU-LI-EVANS-NATURE-2026
7	SOURCE TYPE	Peer-reviewed journal article	classes: PEER_REVIEWED_JOURNAL_ARTICLE
8	INSTITUTIONAL POSITION	Independent academic (Tsinghua University, University of Chicago, Zhongguancun Academy and Santa Fe Institute)	—
9	SCOPE	Biology, medicine, chemistry, physics, materials science and geology; computer science, mathematics and the social sciences excluded	—
10	DESIGN	Bibliometric comparison of adopters and non-adopters; a fine-tuned language model classifies papers as AI-augmented from title and abstract	—
11	SAMPLE / DATASET	41.3 million English-language OpenAlex papers; 310,957 (0.75%) classified as AI-augmented	—
12	MODEL / TOOL / VERSION	AI as a research method, mostly machine learning and deep learning (for example support vector machines and neural networks); not the use of chat assistants for writing	—
13	COMPARATOR	Researchers in the same disciplines who did not publish AI-augmented work	—
14	MAIN RESULT	3.02 times the annual papers; 4.84 times the annual citations; transition to research project leader 1.37 years sooner; classifier F1 0.875 against expert labels	—
15	INFERENTIAL TARGET	Career advantages associated with publishing AI-augmented research in the natural sciences	—
16	DOES NOT LICENSE	A causal effect of adopting AI, a within-person change, or any statement about the social sciences or about chat assistants	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	The authors state they “cannot fully identify the causal linkage between AI adoption and scientific impact”; adopters and non-adopters differ in ways the comparison does not remove; a matched-cohort check in the preprint’s supplement (arXiv version 4; the journal supplement was not read) reports much smaller gaps by career year 10 (24.45% more citations, 9.61% more output); the first preprint version reported different headline numbers	—
19	CONTRADICTORY / SUPPORTING SOURCES	Field-level contraction in the same study: LD09-SL-C02; LLM-era output gains: LD09-SL-C05	—
20	GEOGRAPHY / LANGUAGE	Global / English	—
21	DISTRIBUTIONAL LEDGER	The study cannot say which researchers adopt AI; adoption tracks data-rich fields	—
22	R01 / FIELD-MAP LINKS	LD-09, D3	—
23	WHAT WOULD CHANGE THIS CLAIM?	A causal design (for example staggered access to AI tools) or a replication that includes the social sciences and chat-assistant use	—
24	PUBLICATION STATUS	ELIGIBLE WITH STRONG SCOPE QUALIFIER	state: ELIGIBLE · qualifiers: STRONG_SCOPE
25	RECORDED DATE	2026-10-15	—

Field 22 references resolved against Field Map v0.2: LD-09 (LIVING_DEBATE); D3 (DOMAIN)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026” → Hao et al. (2026), “Artificial intelligence tools expand…” (SRC-SL-HAO-XU-LI-EVANS-NATURE-2026--v1.0) — Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026; class PEER_REVIEWED_JOURNAL_ARTICLE (explicit public provenance pin)

Cited by Living Debate versions

Individual gain, collective narrowing? Does AI make science, creative work and shared knowledge more alike? (v0.1) LD-09

Cite this page

SocioLens project. (2026, October 15). In 41.3 million natural-science papers (1980–2025), researchers who used AI as a research method published 3.02 times as many papers a year, received 4.84 times as many citations and became research project leaders 1.37 years sooner than researchers who did not [Claim LD09-SL-C01, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld09-sl-c01/v1.0/

@misc{sociolens_ld09_sl_c01_v1_0,
  author = {{SocioLens project}},
  title = {In 41.3 million natural-science papers (1980–2025), researchers who used AI as a research method published 3.02 times as many papers a year, received 4.84 times as many citations and became research project leaders 1.37 years sooner than researchers who did not.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld09-sl-c01/v1.0/}},
  note = {Claim LD09-SL-C01, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 cb07f92d739f86832b3094a07ee111f86afaa3a4ccb777ff8d838784b485138d.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD09-SL-C01 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-09 debate; a new Claim, first version, written from the project's LD-09 source notes, checked against full texts or official abstracts. Block “ENTRY 01 — LD09-SL-C01” SHA-256 4a7b00c019fba9bfb826f45fa0a438e01d17543d5ff0103afa1d746a3d43251e; fixture fixtures/authored/claims/LD09-SL-C01--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD09-SL-C01 v1.0); the first version of a new Claim of the LD-09 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD09-SL-C01 v1.0" (Project Lead (Claude, AI), 2026-10-15); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-09 debate; a new Claim, first version, written from the project's LD-09 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-HAO-XU-LI-EVANS-NATURE-2026--v1.0 — basis: field 6 of ENTRY 01 — LD09-SL-C01 cites "Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-HAO-XU-LI-EVANS-NATURE-2026--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Hao, Xu, Li & Evans, “Artificial intelligence tools expand scientists’ impact but contract science’s focus,” Nature, 2026".