Open Access (OA) has emerged as a pivotal driver shaping the dissemination scope and academic impact of research findings. To clarify the impact of publishing models such as open access on the citation performance of biochemical papers, this study selects 177,745 biochemistry professional papers included in the core collection of the Web of Science (WoS CC) as the research data; we conduct an analysis of citation and impact advantages in biochemistry research. Employing correlation analysis, baseline regression modeling, and two-way ANOVA, our analysis indicates that: OA publications in biochemistry exhibit notable citation and impact advantages, which are positively correlated with the degree of openness, and the key determinants of the OA advantage encompass funding sources, reference count, and publication region. At present, China accounts for a disproportionately small proportion of OA papers in this field. In the context of the open-science paradigm, Chinese academic journals must systematically address their developmental bottlenecks and formulate publication innovation strategies to enhance the quality of academic publishing.
OA publications in biochemistry exhibit notable citation and impact advantages, which are positively correlated with the degree of openness
causal-sounding advantage language exceeds the confounded observational design and rests on inconsistently reported regression statistics
the key determinants of the OA advantage encompass funding sources, reference count, and publication region
observational covariates cannot establish determinants, and region is treated inconsistently across the regression and ANOVA analyses
China accounts for a disproportionately small proportion of OA papers in this field
Table 9 directly reports lower Chinese gold-OA uptake than several comparator countries within the selected sample
Derived from the full evaluation — not a separate score.
Strengths
Section 3.1 reports 177,745 articles drawn from 287 selected hybrid journals and provides a screening flowchart. This scale supports detailed descriptive comparisons across OA categories.
↳ Section 3.1 and Figure 1
Comparing OA and non-OA articles within hybrid journals addresses some differences in journal quality, subject scope, and review process that affect cross-journal comparisons.
↳ Introduction and Section 2.1
Section 2.1 presents studies reporting positive, absent, and negative OA citation patterns rather than treating the field as settled.
↳ Section 2.1
Limitations
Tables 5–7 report values labelled as t-statistics whose signs and magnitudes cannot be reconciled with the coefficients and p-values. This prevents reliable interpretation of the main inferential results.
↳ Tables 5–7, pp. 9–10
The regressions adjust for observed bibliometric variables but do not address why authors select OA or differences in article and author quality. The Discussion nevertheless recommends greater OA as a route to higher citations.
↳ Section 3.3 and Discussion, p. 13
The sample is restricted to Q1 hybrid journals in one field-labelled category, and Section 6 cautions against broader generalisation. The policy recommendations on APCs and journal governance extend beyond what this design directly evaluates.
↳ Section 3.1; Discussion; Summary
The hybrid-journal design and large sample provide useful descriptive evidence that OA categories differ in citations and journal-level impact measures. The central regression evidence is substantially weakened by Tables 5–7, where the reported t-statistics cannot be reconciled with coefficients and p-values. The models also leave author and article self-selection into OA unresolved, despite the Discussion framing OA adoption as a route to higher citations. The paper is therefore most informative as a field-specific descriptive study rather than as causal or implementation-ready evidence.
Nabu’s assessment, alongside the field’s view.
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Limited2.4
Confidence mediumRestricting the comparison to hybrid Q1 journals provides a field-specific refinement over cross-journal OA comparisons. The advance remains incremental because the design does not resolve article- and author-level selection into OA.
These papers exhibit high comparability in aspects such as journal quality, subject scope, and review process
The paper reports selection rules, covariates, regression equations, ANOVA, and VIF checks, but observed-covariate adjustment does not identify an OA effect under self-selection. The stacked methodological ceiling also reflects causal conclusions unsupported by this observational design.
researchers... can attempt to achieve higher citations for their papers through a higher degree of OA
The research questions and descriptive-to-regression sequence are generally followable. Precision is reduced by contradictory variable roles and causal language that is stronger than the associative evidence.
statistically significant positive effects of OA adoption
The literature review presents positive, negative, and uncertain findings on OA citation advantage. Section 6 acknowledges omitted variables and unresolved distributional issues, but Section 5 does not carry those qualifications into its practical conclusions.
it is possible that key variables were overlooked
Concerns4 of 4 checks
The principal regression tables contain test-statistic labels or values that cannot be reconciled with the coefficients and significance levels. Several additional contradictions affect the stated model specification and interpretation.
Ethics and consent are appropriately declared not applicable, and funding is disclosed. The data-availability statement does not describe access to the article-level dataset or analysis code needed to reproduce the regressions.
Flags: 2 declared / 5 total
46 of 46 checkable references verified
47 references in manuscript 1 are books, websites or datasets — counted, but not index-checkable
References not verified automatically are resolved manually within 24 hours.
No retraction or expression of concern found in Crossref (includes Retraction Watch).
Sources: Crossref (incl. Retraction Watch) ✓
Where this paper’s evidence sits on the path from initial observation to real-world use.
The evidence consists of retrospective bibliometric associations and does not test an OA intervention or policy implementation. The recommendations therefore require substantial validation before operational use.
Employing correlation analysis, baseline regression modeling, and two-way ANOVA
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