function [data, auxData, metaData, txtData, weights] = mydata_Etrumeus_acuminatus
%% set metadata
metaData.phylum     = 'Chordata'; 
metaData.class      = 'Actinopterygii'; 
metaData.order      = 'Clupeiformes'; 
metaData.family     = 'Dussumieriidae';
metaData.species    = 'Etrumeus_acuminatus'; 
metaData.species_en = 'Red-eye round herring'; 

metaData.ecoCode.climate = {'MB'};
metaData.ecoCode.ecozone = {'MPW'};
metaData.ecoCode.habitat = {'0iMpe', '0iMr'};
metaData.ecoCode.embryo  = {'Mpe'};
metaData.ecoCode.migrate = {'Mo'};
metaData.ecoCode.food    = {'biPz'};
metaData.ecoCode.gender  = {'D'};
metaData.ecoCode.reprod  = {'O'};

metaData.T_typical  = C2K(18); % K, body temp
metaData.data_0     = {'ab'; 'am'; 'Lp'; 'Li'; 'Wwb'; 'Wwp'; 'Wwi'; 'GSI'}; 
metaData.data_1     = {'t-L'; 'L-Ww'}; 

metaData.COMPLETE = 2.5; % using criteria of LikaKear2011

metaData.author    = {'Bas Kooijman'};    
metaData.date_subm = [2025 04 28];              
metaData.email     = {'bas.kooijman@vu.nl'};            
metaData.address   = {'VU University Amsterdam'};  

metaData.curator     = {'Dina Lika'};
metaData.email_cur   = {'lika@uoc.gr'}; 
metaData.date_acc    = [2025 04 28];

%% set data
% zero-variate data;

data.ab = 30;     units.ab = 'd';    label.ab = 'age at birth';              bibkey.ab = 'guess';    
  temp.ab = C2K(18);  units.temp.ab = 'K'; label.temp.ab = 'temperature';
data.am = 6*365;  units.am = 'd';    label.am = 'life span';                 bibkey.am = 'FlorQuin2024';   
  temp.am = C2K(18);  units.temp.am = 'K'; label.temp.am = 'temperature';

data.Lp  = 18.5;   units.Lp  = 'cm';   label.Lp  = 'standard length at puberty'; bibkey.Lp  = 'FlorQuin2024';
data.Li  = 30; units.Li  = 'cm';  label.Li  = 'ultimate standard length';   bibkey.Li  = 'fishbase';

data.Wwb = 1.4e-3; units.Wwb = 'g'; label.Wwb = 'wet weight at birth';   bibkey.Wwb = 'fishbase';
  comment.Wwb = 'based on egg diameter of 1.3-1.47 mm : pi/6*0.138^3';
data.Wwp = 115;   units.Wwp = 'g';    label.Wwp = 'wet weight at puberty';    bibkey.Wwp = {'FlorQuin2024','fishbase'};
  comment.Wwp = 'based on LW and Lp data';
data.Wwi = 489;   units.Wwi = 'g';    label.Wwi = 'ultimate wet weight';    bibkey.Wwi = 'fishbase';
  comment.Wwi = 'based on LW data 283*(30/25)^3; 0.00490*Li^3.08, see F1, gives 174 g';

data.GSI = 0.06; units.GSI = 'g/g';  label.GSI = 'gonado somatic index';    bibkey.GSI = 'guess';
  temp.GSI = C2K(18); units.temp.GSI = 'K'; label.temp.GSI = 'temperature';
  comment.GSI = 'based on Etrumeus_micropus';

% uni-variate data

% time-length
data.tL = [ % time since birth (d), standard length (cm)
0.493	12.346
0.493	12.510
0.500	12.181
0.507	11.852
0.507	12.049
0.507	12.115
0.507	13.432
0.521	14.058
0.729	13.798
0.750	13.370
0.778	13.503
0.986	14.658
0.993	14.066
0.993	14.296
1.006	13.408
1.006	13.868
1.013	13.704
1.013	13.803
1.242	14.827
1.243	15.321
1.249	15.156
1.256	14.235
1.256	15.058
1.256	15.584
1.263	14.432
1.270	14.564
1.492	15.918
1.499	14.535
1.499	15.556
1.506	14.700
1.506	15.325
1.506	15.753
1.513	14.864
1.513	15.227
1.513	16.083
1.520	15.062
1.749	15.922
1.769	15.790
1.769	16.120
1.776	16.416
1.991	16.255
1.999	17.407
1.999	17.506
1.999	17.704
1.999	17.770
2.005	17.210
2.012	16.881
2.026	16.025
2.026	16.585
2.241	16.259
2.248	16.885
2.248	17.016
2.255	16.457
2.255	16.621
2.255	17.280
2.255	17.313
2.261	16.062
2.261	16.391
2.262	18.004
2.276	17.577
2.490	16.691
2.491	18.041
2.497	17.350
2.497	17.481
2.498	18.996
2.504	16.889
2.505	17.712
2.505	17.844
2.505	17.877
2.505	18.634
2.505	18.700
2.505	18.766
2.511	16.527
2.511	16.560
2.511	16.988
2.518	17.251
2.726	17.518
2.747	18.276
2.747	18.506
2.754	18.012
2.754	18.078
2.754	18.671
2.761	18.770
2.761	19.033
2.768	17.683
2.768	17.782
2.989	17.457
2.996	17.259
2.997	19.103
2.997	19.399
3.004	18.148
3.004	18.280
3.004	18.412
3.004	18.543
3.004	18.675
3.004	18.905
3.004	19.333
3.004	19.959
3.010	17.720
3.010	17.720
3.010	17.885
3.011	18.774
3.011	19.663
3.239	18.712
3.239	18.909
3.246	17.560
3.246	17.922
3.246	18.778
3.254	19.436
3.267	17.790
3.267	18.153
3.267	18.317
3.267	18.449
3.267	18.515
3.489	19.704
3.495	17.926
3.496	19.407
3.496	20.000
3.496	20.132
3.509	18.124
3.510	19.539
3.510	19.836
3.524	19.243
3.530	18.387
3.530	18.618
3.530	18.848
3.738	19.345
3.738	19.378
3.739	19.609
3.739	19.708
3.739	20.597
3.739	20.827
3.745	18.786
3.746	19.971
3.746	20.103
3.746	20.300
3.746	21.156
3.752	19.049
3.752	19.214
3.766	18.655
3.995	20.535
3.995	20.700
3.996	21.193
4.002	20.996
4.009	18.988
4.009	19.416
4.009	19.975
4.009	20.305
4.009	20.864
4.010	21.490
4.016	19.646
4.016	20.140
4.022	19.251
4.023	19.745
4.029	18.758
4.238	21.263
4.238	21.461
4.245	21.197
4.251	19.156
4.251	19.222
4.251	19.321
4.251	19.584
4.252	20.210
4.252	20.605
4.252	21.955
4.258	19.683
4.259	20.408
4.259	20.473
4.259	20.704
4.259	20.901
4.265	19.848
4.501	20.675
4.501	20.708
4.501	20.840
4.501	21.103
4.501	21.136
4.501	21.366
4.502	21.893
4.508	20.181
4.508	20.280
4.508	21.498
4.515	19.852
4.515	19.918
4.522	20.445
4.522	20.972
4.523	21.992
4.744	21.272
4.750	19.823
4.751	21.140
4.757	19.527
4.764	20.778
4.765	20.877
4.993	20.288
4.993	21.539
4.994	22.428
4.994	22.658
5.000	21.012
5.001	21.868
5.001	22.132
5.007	21.243
5.007	21.473
5.007	21.737
5.492	20.922
5.500	23.062
5.506	22.074
5.507	22.864
5.514	22.568
5.742	22.012
5.742	22.012
5.742	22.638
5.749	22.144
5.749	22.506
5.749	23.329
5.749	23.395
5.999	23.663
6.006	23.301
6.006	23.959
6.012	22.774
6.019	21.918
6.019	22.116
6.019	22.280
6.019	22.511
6.020	24.190
6.020	25.079];
data.tL(:,1) = 365 * (2.1 + data.tL(:,1)); % convert yr to d
for i=2:size(data.tL,1); if data.tL(i,1)<=data.tL(i,1);data.tL(i,1)=data.tL(i,1)+1e-3;end;end
units.tL = {'d', 'cm'};  label.tL = {'time since birth', 'standard length'};  
temp.tL = C2K(18);  units.temp.tL = 'K'; label.temp.tL = 'temperature';
bibkey.tL = 'FlorQuin2024';

% length-weight
data.LW = [ ... % std length (cm), weight (g)
12.464	33.495
13.460	43.013
13.474	53.119
13.515	39.226
13.979	53.142
14.019	49.354
14.033	44.302
14.088	48.726
14.101	61.990
14.129	51.254
14.224	53.785
14.279	49.366
14.388	56.318
14.388	46.845
14.429	51.267
14.470	56.322
14.497	53.165
14.511	63.903
14.552	62.641
14.593	56.959
14.647	62.014
14.688	54.437
14.729	58.860
14.756	54.440
14.797	60.758
14.797	62.021
14.865	56.340
14.906	53.184
14.947	64.554
14.988	77.187
15.002	57.609
15.002	60.767
15.016	68.978
15.029	51.926
15.070	70.244
15.097	62.666
15.179	60.775
15.248	67.094
15.261	55.726
15.302	74.675
15.329	61.413
15.357	72.151
15.398	62.048
15.439	68.997
15.507	78.474
15.520	57.001
15.520	74.054
15.561	64.582
15.575	65.845
15.575	60.161
15.589	75.951
15.589	85.425
15.657	79.112
15.671	71.534
15.712	81.641
15.780	81.013
15.780	67.749
15.807	60.803
15.834	76.594
15.834	66.489
15.848	72.805
15.875	77.859
15.943	86.073
15.984	69.653
15.984	62.706
15.998	76.601
15.998	75.970
16.012	60.813
16.012	80.392
16.025	68.392
16.053	77.235
16.135	76.608
16.162	82.293
16.216	72.822
16.216	79.769
16.230	84.822
16.285	86.088
16.326	75.353
16.366	89.250
16.366	85.460
16.366	81.039
16.448	80.411
16.462	91.149
16.462	75.359
16.517	69.046
16.571	80.417
16.585	85.470
16.598	76.629
16.612	93.050
16.626	89.261
16.653	87.368
16.708	81.686
16.721	94.950
16.721	82.950
16.789	91.163
16.803	86.111
16.830	96.850
16.871	96.851
16.912	72.222
16.940	88.644
16.967	82.329
16.994	86.120
16.994	95.594
16.994	96.225
17.008	101.279
17.062	94.334
17.103	79.809
17.117	75.389
17.131	91.810
17.144	101.285
17.144	77.916
17.172	105.707
17.172	94.970
17.226	96.867
17.240	86.131
17.253	104.448
17.253	100.026
17.253	76.658
17.308	89.924
17.308	85.503
17.363	101.926
17.376	95.611
17.376	81.085
17.444	93.088
17.444	103.825
17.485	88.669
17.526	98.776
17.554	81.724
17.554	108.251
17.595	88.042
17.622	100.043
17.622	94.359
17.635	106.360
17.676	112.677
17.690	98.151
17.704	84.889
17.717	103.205
17.772	105.103
17.772	97.524
17.813	107.631
17.908	115.845
17.977	101.322
17.977	122.164
17.990	111.428
18.018	98.798
18.018	105.745
18.031	109.535
18.099	91.854
18.140	103.856
18.209	115.859
18.209	111.438
18.209	95.649
18.277	97.546
18.290	110.179
18.331	114.601
18.372	123.445
18.400	108.920
18.441	120.291
18.468	134.818
18.481	115.240
18.495	127.872
18.522	98.189
18.550	117.138
18.563	123.454
18.577	108.297
18.577	100.718
18.591	129.771
18.632	131.668
18.632	127.247
18.632	114.615
18.673	108.301
18.700	119.039
18.741	124.094
18.782	125.990
18.809	122.202
18.809	137.360
18.850	120.309
18.877	113.994
18.891	108.942
18.973	132.315
18.973	102.630
18.986	121.578
19.000	138.632
19.000	114.000
19.000	110.842
19.027	143.054
19.027	127.264
19.041	118.423
19.055	128.529
19.068	102.635
19.109	132.952
19.164	122.218
19.177	128.534
19.205	129.799
19.205	141.799
19.218	117.799
19.259	144.327
19.314	132.962
19.327	148.120
19.327	141.173
19.327	119.699
19.355	131.069
19.382	146.859
19.396	119.070
19.423	135.493
19.478	151.285
19.491	132.970
19.491	115.917
19.505	146.233
19.505	138.654
19.505	124.128
19.519	162.023
19.532	130.445
19.573	151.289
19.573	140.552
19.587	159.500
19.628	157.607
19.628	139.291
19.655	153.819
19.682	129.189
19.710	144.348
19.791	120.352
19.791	140.562
19.819	148.142
19.860	155.091
19.887	142.461
19.969	158.254
19.982	137.413
19.982	123.518
19.996	153.834
20.010	144.993
20.010	150.677
20.010	126.046
20.037	168.363
20.051	150.047
20.051	132.363
20.133	157.630
20.187	164.580
20.201	162.686
20.228	153.845
20.283	148.163
20.310	150.691
20.310	143.743
20.324	175.954
20.351	155.114
20.378	161.431
20.378	136.799
20.405	172.169
20.419	199.959
20.419	133.643
20.446	146.276
20.460	160.803
20.487	148.804
20.487	156.383
20.515	182.910
20.528	143.753
20.528	139.332
20.556	181.018
20.569	168.387
20.583	173.440
20.583	157.019
20.596	183.546
20.596	170.914
20.596	151.967
20.637	162.074
20.733	150.710
20.733	162.710
20.733	172.183
20.760	179.132
20.788	153.870
20.788	187.344
20.801	142.502
20.801	145.029
20.815	162.713
20.828	170.293
20.897	156.401
20.938	168.403
20.951	146.930
20.951	170.299
20.951	179.772
20.951	196.193
20.979	160.826
20.992	133.669
20.992	181.037
21.019	167.775
21.019	189.249
21.047	146.934
21.047	163.356
21.060	156.409
21.060	142.514
21.060	128.619
21.074	174.725
21.088	217.042
21.101	129.253
21.170	161.466
21.183	152.625
21.197	146.941
21.224	184.837
21.251	164.628
21.279	157.682
21.292	153.893
21.306	198.736
21.361	173.475
21.442	179.794
21.456	188.006
21.470	167.796
21.470	177.901
21.483	169.691
21.483	167.165
21.511	186.113
21.511	209.482
21.552	186.115
21.552	192.431
21.606	162.118
21.606	193.697
21.634	204.435
21.661	168.436
21.702	205.069
21.715	156.438
21.729	172.860
21.852	127.392
21.893	209.499
21.906	218.973
21.961	182.976
21.988	201.293
21.988	214.556
22.002	222.767
22.016	170.978
22.016	207.610
22.029	177.295
22.029	191.821
22.029	218.347
22.043	202.558
22.220	178.566
22.248	206.357
22.261	220.252
22.275	215.200
22.302	192.465
22.316	224.044
22.316	187.413
22.357	212.046
22.370	197.520
22.384	193.732
22.452	235.419
22.452	227.840
22.480	212.683
22.493	224.052
22.493	188.052
22.493	181.105
22.493	165.315
22.548	192.476
22.602	216.478
22.630	229.743
22.821	223.436
22.957	179.231
22.998	235.444
23.012	215.234
23.039	226.603
23.066	251.868
23.203	232.926
23.271	211.456
23.298	235.457
23.489	251.255
24.185	238.023
24.786	197.629
25.031	233.009
25.113	197.644];
units.LW = {'cm', 'g'};  label.LW = {'standard length','weight'};  
bibkey.LW = 'FlorQuin2024';
    
%% set weights for all real data
weights = setweights(data, []);
weights.tL = 5 * weights.tL;
weights.Li = 2 * weights.Li;
weights.Wwb = 2 * weights.Wwb;
weights.Wwi = 2 * weights.Wwi;
weights.ab = 0 * weights.ab;

%% set pseudodata and respective weights
[data, units, label, weights] = addpseudodata(data, units, label, weights);

%% pack auxData and txtData for output
auxData.temp = temp;
txtData.units = units;
txtData.label = label;
txtData.bibkey = bibkey;
txtData.comment = comment;

%% Discussion points
D1 = 'Temperatures are guessed';
D2 = 'I had to add 2 yrs to age-estimates in tL data to arrive at a reasonable fit';
metaData.discussion = struct('D1',D1, 'D2',D2);

%% Facts
F1 = 'length-weight: W in g = 0.00490*(TL in cm)^3.08';
metaData.bibkey.F1 = 'fishbase'; 
F2 = 'Eastern Pacific: Monterey Bay (California, USA) to Chile';
metaData.bibkey.F2 = 'fishbase'; 
metaData.facts = struct('F1',F1, 'F2',F2);

%% Links
metaData.links.id_CoL = '6GT79'; % Cat of Life
metaData.links.id_ITIS = '161746'; % ITIS
metaData.links.id_EoL = '40054022'; % Ency of Life
metaData.links.id_Wiki = 'Etrumeus'; % Wikipedia
metaData.links.id_ADW = 'Etrumeus_acuminatus'; % ADW
metaData.links.id_Taxo = '376025'; % Taxonomicon
metaData.links.id_WoRMS = '308314'; % WoRMS
metaData.links.id_fishbase = 'Etrumeus_acuminatus'; % fishbase

%% References
bibkey = 'Wiki'; type = 'Misc'; bib = ...
'howpublished = {\url{http://en.wikipedia.org/wiki/Etrumeus_acuminatus}}';
metaData.biblist.(bibkey) = ['''@', type, '{', bibkey, ', ' bib, '}'';'];
%
bibkey = 'Kooy2010'; type = 'Book'; bib = [ ...  % used in setting of chemical parameters and pseudodata
'author = {Kooijman, S.A.L.M.}, ' ...
'year = {2010}, ' ...
'title  = {Dynamic Energy Budget theory for metabolic organisation}, ' ...
'publisher = {Cambridge Univ. Press, Cambridge}, ' ...
'pages = {Table 4.2 (page 150), 8.1 (page 300)}, ' ...
'howpublished = {\url{../../../bib/Kooy2010.html}}'];
metaData.biblist.(bibkey) = ['''@', type, '{', bibkey, ', ' bib, '}'';'];
%
bibkey = 'FlorQuin2024'; type = 'Article'; bib = [ ...
'doi = {10.3856/vol52-issue5-fulltext-3201}, ' ...
'author = {Ricardo Javier Flores-Anaya and Casimiro Qui\~{n}onez-Vel\''{a}zquez and Dana Isela Arizmendi-Rodríguez and Xchel Gabriel Moreno-S\''{a}nchez}, ' ... 
'year = {2024}, ' ...
'title = {Estimation of age, growth, and length at first maturity of the round herring \emph{Etrumeus acuminatus} ({G}ilbert, 1890) on the western coast of {B}aja {C}alifornia Sur, {M}exico}, ' ...
'journal = {Latin American Journal of Aquatic Research}, ' ...
'volume = {52(5)}, ' ...
'pages = {1713-726}'];
metaData.biblist.(bibkey) = ['''@', type, '{', bibkey, ', ' bib, '}'';'];
%
bibkey = 'fishbase'; type = 'Misc'; bib = ...
'howpublished = {\url{https://www.fishbase.de/summary/Etrumeus_acuminatus.html}}';
metaData.biblist.(bibkey) = ['''@', type, '{', bibkey, ', ' bib, '}'';'];
  
  
