diff --git a/scoping_review.qmd b/scoping_review.qmd
index 64e5330..8f27091 100644
--- a/scoping_review.qmd
+++ b/scoping_review.qmd
@@ -46,13 +46,13 @@ bib_string=""
 for partial_bib in RAW_DATA.glob("**/*.bib"):
     with open(partial_bib) as f:
         bib_string+="\n".join(f.readlines())
-sample_raw = bibtexparser.parse_string(bib_string)
+bib_sample_raw_db = bibtexparser.parse_string(bib_string)
 
 bib_string=""
 for partial_bib in WORKING_DATA.glob("**/*.bib"):
     with open(partial_bib) as f:
         bib_string+="\n".join(f.readlines())
-sample = bibtexparser.parse_string(bib_string)
+bib_sample = bibtexparser.parse_string(bib_string)
 ```
 
 # Introduction
@@ -388,22 +388,17 @@ and the sources will be added to the sample to undergo the same screening proces
 #| echo: false
 #| output: asis
 
-sample_out_title = []
-sample_out_abstract = []
-sample_out_fulltext = []
-sample_out_language = []
-sample_relvant_done = []
+FULL_RAW_SAMPLE_NOTHING_REMOVED = 2396
+nr_database_query_raw = len(bib_sample_raw_db.entries)
+nr_out_duplicates = FULL_RAW_SAMPLE_NOTHING_REMOVED - len(bib_sample.entries)
+nr_other_sources = (len(bib_sample.entries) + nr_out_duplicates) - nr_database_query_raw
 
-for e in sample.entries:
-    if "keywords" in e.fields_dict.keys():
-        if "out::title" in e["keywords"]:
-            sample_out_title.append(e)
-        elif "out::abstract" in e["keywords"]:
-            sample_out_abstract.append(e)
-        elif "out::full-text" in e["keywords"]:
-            sample_out_fulltext.append(e)
-        elif "done::extracted" in e["keywords"] and "relevant" in e["keywords"]:
-            sample_relvant_done.append(e)
+all_keywords = [entry["keywords"] for entry in bib_sample.entries if "keywords" in entry.fields_dict.keys()]
+nr_out_title = len([1 for kw in all_keywords if "out::title" in kw])
+nr_out_abstract = len([1 for kw in all_keywords if "out::abstract" in kw])
+nr_out_fulltext = len([1 for kw in all_keywords if "out::full-text" in kw])
+nr_out_language = len([1 for kw in all_keywords if "out::language" in kw])
+nr_extraction_done = len([1 for kw in all_keywords if "done::extracted" in kw])
 
 t3 = "`" * 3
 # FIXME use 02-data/supplementary undeduplciated counts to get database starting and snowballing counts
@@ -414,18 +409,18 @@ print(f"""
 %%| fig-cap: "Sample sorting process through identification and screening"
 %%| fig-width: 6
 flowchart TD;
-    search_db["Records identified through database searching (n=1643)"] --> starting_sample;
-    search_prev["Records identified through other sources (n=753)"] --> starting_sample["Starting sample (n=2396)"];
+    search_db["Records identified through database searching (n={nr_database_query_raw})"] --> starting_sample;
+    search_prev["Records identified through other sources (n={nr_other_sources})"] --> starting_sample["Starting sample (n={FULL_RAW_SAMPLE_NOTHING_REMOVED})"];
 
-    starting_sample -- "Duplicate removal ({2396 - len(sample.entries)} removed) "--> dedup["Records after duplicates removed (n={len(sample.entries)})"];
+    starting_sample -- "Duplicate removal ({nr_out_duplicates} removed) "--> dedup["Records after duplicates removed (n={len(bib_sample.entries)})"];
 
-    dedup -- "Title screening ({len(sample_out_title)} excluded)" --> title_screened["Records after titles screened (n={len(sample.entries)-len(sample_out_title)})"];
+    dedup -- "Title screening ({nr_out_title} excluded)" --> title_screened["Records after titles screened (n={len(bib_sample.entries) - nr_out_title})"];
 
-    title_screened -- "Abstract screening ({len(sample_out_abstract)} excluded)"--> abstract_screened["Records after abstracts screened (n={len(sample.entries)-len(sample_out_title)-len(sample_out_abstract)}"];
+    title_screened -- "Abstract screening ({nr_out_abstract} excluded)"--> abstract_screened["Records after abstracts screened (n={len(bib_sample.entries)-nr_out_title-nr_out_abstract}"];
 
-    abstract_screened -- "  Language screening ({len(sample_out_language)} excluded)  "--> language_screened["Records after language screened (n={len(sample.entries)-len(sample_out_title)-len(sample_out_abstract)-len(sample_out_language)})"];
+    abstract_screened -- "  Language screening ({nr_out_language} excluded)  "--> language_screened["Records after language screened (n={len(bib_sample.entries)-nr_out_title-nr_out_abstract-nr_out_language})"];
 
-    language_screened -- "  Full-text screening ({len(sample_out_fulltext)} excluded)  "--> full-text_screened["Full-text articles assessed for eligibility (n={len(sample_relvant_done)})"];
+    language_screened -- "  Full-text screening ({nr_out_fulltext} excluded)  "--> full-text_screened["Full-text articles assessed for eligibility (n={nr_extraction_done})"];
 {t3}
 """)
 ```
@@ -437,18 +432,13 @@ The results to be identified in the matrix include a study’s: i) key outcome m
 
 ```{python}
 #| echo: false
-
-sample_size_all = len(sample_raw.entries)
-
-sample_relevant = []
-for e in sample.entries:
-    if "keywords" in e.fields_dict.keys() and "relevant" in e["keywords"]:
-        sample_relevant.append(e)
+# TODO Remove redundant 'relevant' studies observation below once all studies are extracted.
+nr_relevant = len([1 for kw in all_keywords if "relevant" in kw])
 
 md(f"""
-The query execution results in an initial sample of {sample_size_all} potential studies after the identification process.
+The query execution results in an initial sample of {nr_database_query_raw} potential studies identified from the database search as well as {nr_other_sources} potential studies from other sources, leading to a total initial number of {FULL_RAW_SAMPLE_NOTHING_REMOVED}.
 This accounts for all identified studies without duplicate removal, without controlling for literature that has been superseded or applying any other screening criteria.
-Of these, {len(sample_relevant)} have been identified as relevant studies for the purposes of this scoping review.
+Of these, {nr_relevant} have been identified as potentially relevant studies for the purposes of this scoping review, from which {nr_extraction_done} have been extracted.
 """)
 ```