A reply to: “Response to Comment on “Density Functional Theory and 3D-RISM-KH molecular theory of solvation studies of CO2 reduction on Cu-, Cu2O-, Fe-, and Fe3O4-based nanocatalysts””
Bibliographic record
Abstract
In response (Kovalenko and Neburchilov, J. Mol. MODEL: 28:33, 1) to the comment (Gusarov, J. Mol. MODEL: reduction reaction studied by Kovalenko and Neburchilov (J. Mol. MODEL: 26:267-276, 3). The intermediate products of this reaction are well known and presented in the literature including the studies of Li and Kanan (J. Am. Chem. Soc. 134:7231-7234, 4); Feaster et al. (ACS Catal. 7:4822-4827, 5); Choi et al. (Sci. Rep. 7:41,207-41,210, 6); Kuhl et al. (Am. Chem. Soc. 136:14,107-14,113, 7); Kuhl et al. (Energy Environ. Sci. 5:7050-7059, 8); and Hatsukade et al. (Phys. Chem. Chem. Phys. 16:13,814-13,819, 9) referenced by Kovalenko and Neburchilov (J. Mol. MODEL: 26:267-276, 3). In particular, in Figs. 2(d), 3(d), 4(d), and 5(d) (Kovalenko and Neburchilov, J. Mol. MODEL: 26:267-276, 3), the orientation of carbon monoxide is opposite to Fig. 4 (Feaster et al., ACS Catal. 7:4822-4827, 5), Fig. 6(a) (Choi et al., Sci. Rep. 7:41,207-41,210, 6), Fig. 7 (Kuhl et al., Energy Environ. Sci. 5:7050-7059, 8), Fig. 7 (Hatsukade et al., Phys. Chem. Chem. Phys. 16:13,814-13,819, 9), and Fig. 2 (Gusarov, J. Mol. MODEL: 27:344-354, 2). This obvious fact which also comes from chemical properties of components should not be ignored.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.044 | 0.053 |
| Insufficient payload (model declined to judge) | 0.017 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".