docs: update comment and add comment

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

Author: kgryte

lib/node_modules/@stdlib/blas/base/dger/lib/base.js

@@ -75,7 +75,7 @@ var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
 *
 *     As may be observed, `A` stored in column-major order is equivalent to storing the transpose of `A` in row-major order, and storing `A` in row-major order is equivalent to storing the transpose of `A` in column-major order, and vice versa.
 *
-*     Hence, we can interpret an `M` by `N` row-major matrix `B` as the matrix `A^T` stored in column-major. In which case, we can derive an update equation for `B` as follows:
+*     Hence, we can interpret an `M` by `N` row-major matrix `B` as the matrix `A^T` stored in column-major order. In which case, we can derive an update equation for `B` as follows:
 *
 *     ```tex
 *     \begin{align*}
@@ -88,7 +88,7 @@ var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
 *     \end{align*}
 *     ```
 *
-*     Accordingly, we can reuse the same loop logic for column-major and row-major `A` by simply swapping `x` and `y` and `M` and `N` when `A` is row-major. That is the essence of loop interchange.
+*     Accordingly, we can reuse the same loop logic for column-major and row-major `A` by simply swapping `x` and `y` and `M` and `N` when `A` is row-major order. That is the essence of loop interchange.
 *
 * @private
 * @param {NonNegativeInteger} M - number of rows in the matrix `A`
@@ -164,6 +164,7 @@ function dger( M, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA
 	iy = offsetY;
 	ia = offsetA;
 	for ( i1 = 0; i1 < S1; i1++ ) {
+		// Check whether we can avoid the inner loop entirely...
 		if ( y[ iy ] === 0.0 ) {
 			ia += da0 * S0;
 		} else {