unable to cross ref for quarto bug

Code/.gitignore

@@ -0,0 +1 @@
+/.luarc.json

Data/1_Writing/1_Task/1_Introduction copy.qmd

@@ -0,0 +1,18 @@
+# Introduction {#sec-chap_1_Intro}
+In this work, a tool called \glsfirst{cnmc} is further developed.
+The overall goal, in very brief terms, is to generate a model, which is able to 
+predict the trajectories of general dynamical systems. The model
+shall be capable of predicting the trajectories when a model parameter
+value is changed. 
+Some basics about dynamical systems are covered in 
+subsection [-@sec-subsec_1_1_1_Principles] and in-depth explanations about \gls{cnmc} are given in
+chapter [-@sec-chap_2_Methodology]. \newline 
+
+However, for a short and broad introduction to \gls{cnmc} the workflow depicted in figure @fig-fig_1_CNMC_Workflow shall be highlighted. 
+The input it receives is data of a dynamical system or space state vectors for a range of model parameter values. The two main important outcomes are some accuracy measurements and the predicted trajectory for each desired model parameter value.
+Any inexperienced user may only have a look at the predicted trajectories to 
+quickly decide visually whether the prediction matches the trained data. Since \gls{cnmc} is written in a modular manner, meaning it can be regarded as 
+a black-box function, it can easily be integrated into other existing codes or 
+workflows. \newline
+
+![Broad overview: Workflow of \gls{cnmc}](../../3_Figs_Pyth/1_Task/1_CNMc_1.svg){#fig-fig_1_CNMC_Workflow}

Data/1_Writing/1_Task/1_Introduction.qmd

@@ -1,23 +1,9 @@
-
+# Chap Test_4 {#sec-chap_1_Abc}
+Here is some more text
 
 # Introduction {#sec-chap_1_Intro}
-In this work, a tool called \glsfirst{cnmc} is further developed.
-The overall goal, in very brief terms, is to generate a model, which is able to 
-predict the trajectories of general dynamical systems. The model
-shall be capable of predicting the trajectories when a model parameter
-value is changed. 
-Some basics about dynamical systems are covered in 
-subsection [-@sec-subsec_1_1_1_Principles] and in-depth explanations about \gls{cnmc} are given in
-chapter [-@sec-chap_2_Methodlogy]. \newline 
-
-However, for a short and broad introduction to \gls{cnmc} the workflow depicted in figure @fig-fig_1_CNMC_Workflow shall be highlighted. 
-
+Here is some more text
 
-The input it receives is data of a dynamical system or space state vectors for a range of model parameter values. The two main important outcomes are some accuracy measurements and the predicted trajectory for each desired model parameter value.
-Any inexperienced user may only have a look at the predicted trajectories to 
-quickly decide visually whether the prediction matches the trained data. Since \gls{cnmc} is written in a modular manner, meaning it can be regarded as 
-a black-box function, it can easily be integrated into other existing codes or 
-workflows. \newline
 
-![Broad overview: Workflow of \gls{cnmc}](../../3_Figs_Pyth/1_Task/1_CNMc_1.svg){#fig-fig_1_CNMC_Workflow}
 
+It does work when first the ids are defined like first: chap_1_Abc and then chap_1_Intro. In that case the chap_1_Abc is not able to be referenced

Data/1_Writing/1_Task/4_CNMc.qmd

@@ -6,7 +6,7 @@ Also, in the latter, the main idea was to predict the trajectories
 for dynamical systems with a control term or a model parameter value $\beta$. 
 In this subsection, a review of 
 [@Max2021] shall be given with pointing out which parts need to be improved. In addition, some distinctions between the previous version of \gls{cnmc} and the most recent version are named. 
-Further applied modifications are provided in chapter [-@sec-chap_2_Methodlogy].\newline
+Further applied modifications are provided in chapter [-@sec-chap_2_Methodology].\newline
 
 To avoid confusion between the \gls{cnmc} version described in this thesis and the prior \gls{cnmc} version, the old version will be referred to as *first CNMc*. 
 *First CNMc* starts by defining a range of model parameter values

Data/1_Writing/2_Task/0_Methodlogy.qmd

@@ -1,4 +1,4 @@
-# Methodology {#sec-chap_2_Methodlogy}
+# Methodology {#sec-chap_2_Methodology}
 In this chapter, the entire pipeline for designing the proposed
 \gls{cnmc} is elaborated. For this purpose, the ideas behind 
 the individual processes are explained. 

trials.qmd

@@ -1,14 +1,41 @@
-# Trials {.unnumbered}
-asdasd
-Thissince \gls{cnmc} 
-Hello thre
-
-## ANd some more
-asdad
-asd
-ad
-asf
-as
+# Trials {#sec-chap_1_Test}
+In this work, a tool called \glsfirst{cnmc} is further developed.
+The overall goal, in very brief terms, is to generate a model, which is able to 
+predict the trajectories of general dynamical systems. The model
+shall be capable of predicting the trajectories when a model parameter
+value is changed. 
+Some basics about dynamical systems are covered in 
+subsection [-@sec-subsec_1_1_1_Principles] and in-depth explanations about \gls{cnmc} are given in
+chapter [-@sec-chap_1_Test]. \newline 
+
+chapter [-@sec-chap_2_Test]
+chapter [-@sec-chap_1_Test_2]
+chapter [-@sec-chap_1_Test_3]
+chapter [-@sec-chap_1_Intro]\newline
+
+
+Intra reference:  [-@sec-chap_1_Intra]\newline
+
+Intro reference:  [-@sec-chap_1_Intro]\newline 
+
+chapter [-@sec-chap_1_Abc]\newline 
+
+
+
+
+# Chap Test {#sec-chap_2_Test}
+Here is some more text
+
+# Chap Test_2 {#sec-chap_1_Test_2}
+Here is some more text
+
+# Chap Test_3 {#sec-chap_1_Test_3}
+Here is some more text
+
+
+Further check [@sec-chap_1_Intro] -- is found now (able to resolve crossref) 
+
+chapter [-@sec-chap_1_Abc] -- now this becomes the issue (will not be found anymore)
 
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