function [data, auxData, metaData, txtData, weights] = mydata_Micromesistius_australis
%% set metadata
metaData.phylum     = 'Chordata'; 
metaData.class      = 'Actinopterygii'; 
metaData.order      = 'Gadiformes'; 
metaData.family     = 'Gadidae';
metaData.species    = 'Micromesistius_australis'; 
metaData.species_en = 'Southern blue whiting'; 

metaData.ecoCode.climate = {'MC'};
metaData.ecoCode.ecozone = {'MASW', 'MPSE'};
metaData.ecoCode.habitat = {'0jMp', 'jiMd'};
metaData.ecoCode.embryo  = {'Mp'};
metaData.ecoCode.migrate = {'Mo'};
metaData.ecoCode.food    = {'bjPz', 'jiCi', 'jiCvf'};
metaData.ecoCode.gender  = {'D'};
metaData.ecoCode.reprod  = {'O'};

metaData.T_typical  = C2K(6); % in K, body temp
metaData.data_0     = {'ab'; 'ap'; 'am'; 'Lp'; 'Li'; 'Wwb'; 'Wwp'; 'Wwi'; 'GSI'};  
metaData.data_1     = {'t-L'}; 

metaData.COMPLETE = 2.4; % using criteria of LikaKear2011

metaData.author   = {'Bas Kooijman'}; 
metaData.date_subm = [2019 01 15]; 
metaData.email    = {'bas.kooijman@vu.nl'}; 
metaData.address  = {'VU University, Amsterdam'};

metaData.author_mod_1   = {'Bas Kooijman'};    
metaData.date_mod_1     = [2023 04 03];              
metaData.email_mod_1    = {'bas.kooijman@vu.nl'};            
metaData.address_mod_1  = {'VU University, Amsterdam'};   

metaData.curator     = {'Starrlight Augustine'};
metaData.email_cur   = {'starrlight@tecnico.ulisboa.pt'}; 
metaData.date_acc    = [2023 04 03];

%% set data
% zero-variate data
data.ab = 10;  units.ab = 'd';    label.ab = 'age at birth';                   bibkey.ab = 'guess'; 
  temp.ab = C2K(9.1); units.temp.ab = 'K'; label.temp.ab = 'temperature';
  comment.ab = 'based on Merluccius hubbsi';
data.tp = 2*365;  units.tp = 'd';    label.tp = 'time since birth at puberty for female'; bibkey.tp = {'ContArel2014','fishbase'}; 
  temp.tp = C2K(6); units.temp.tp = 'K'; label.temp.tp = 'temperature';
  comment.tp = 'based on interpolation of Lp in tL_f data';
data.am = 25*365;     units.am = 'd';    label.am = 'life span';               bibkey.am = 'ContArel2014';  
  temp.am = C2K(6); units.temp.am = 'K'; label.temp.am = 'temperature';

data.Lp = 37;     units.Lp = 'cm';   label.Lp = 'total length at puberty for females';  bibkey.Lp = 'fishbase';
  comment.Lp = '33 to 40 cm';
data.Li = 90;    units.Li = 'cm';   label.Li = 'ultimate total length';       bibkey.Li = 'fishbase';

data.Wwb = 3.4e-4;  units.Wwb = 'g';   label.Wwb = 'wet weight at birth';      bibkey.Wwb = 'guess';
  comment.Wwb = 'based on egg diameter of 866 mum for Merluccius hubbsi: pi/6*0.0866^3';
data.Wwp = 94;  units.Wwp = 'g';   label.Wwp = 'wet weight at puberty';        bibkey.Wwp = 'guess';
  comment.Wwp = 'based on (Lp/Li)^3*Wwi';
data.Wwi = 1350;  units.Wwi = 'g';   label.Wwi = 'ultimate wet weight';        bibkey.Wwi = 'fishbase';
  
data.GSI = 25; units.GSI = 'g/g';  label.GSI = 'gonado somatic index'; bibkey.GSI = 'guess';
  temp.GSI = C2K(6); units.temp.GSI = 'K'; label.temp.GSI = 'temperature'; 
  comment.GSI = 'based on Merluccius_hubbsi';

% uni-variate data
% time-length
data.tL_f = [ ... % year class (yr), total length (cm)
0.956	24.667
0.956	25.879
1.002	20.909
1.002	22.121
1.002	23.091
1.002	26.970
1.047	32.303
1.913	29.273
1.913	30.848
1.958	27.697
1.958	30.000
1.958	31.576
2.004	26.727
2.004	32.667
2.004	33.273
2.004	36.303
2.004	37.030
2.004	38.848
2.049	22.848
2.049	24.061
2.095	24.909
2.095	25.636
2.140	34.970
2.186	34.242
2.914	42.848
2.960	28.182
2.960	29.152
2.960	38.727
2.960	39.576
3.005	38.121
3.005	44.788
3.051	25.030
3.051	26.000
3.051	27.212
3.051	30.364
3.051	31.818
3.051	32.909
3.051	33.758
3.051	34.485
3.051	35.212
3.051	35.818
3.051	36.545
3.051	37.515
3.051	41.030
3.916	38.485
3.962	28.061
3.962	29.030
3.962	30.121
3.962	31.333
3.962	37.030
3.962	41.030
3.962	47.818
3.962	48.909
3.962	56.061
3.962	62.848
4.007	31.818
4.007	32.788
4.007	34.121
4.007	34.970
4.007	36.182
4.007	39.455
4.007	40.303
4.007	41.879
4.007	42.848
4.007	43.818
4.007	46.727
4.053	44.667
4.098	45.879
4.872	49.758
4.918	44.788
4.918	45.394
4.918	50.727
4.918	51.576
4.964	30.848
4.964	37.152
4.964	38.000
4.964	38.848
4.964	39.818
4.964	41.879
4.964	42.606
4.964	43.333
4.964	43.818
4.964	46.848
5.009	34.000
5.009	34.727
5.009	35.818
5.009	40.909
5.009	48.909
5.009	55.697
5.055	47.939
5.965	35.212
5.965	35.939
5.965	36.667
5.965	37.758
5.965	38.606
5.965	39.455
5.965	40.182
5.965	44.667
5.965	45.515
5.965	46.242
5.965	49.152
5.965	54.242
6.011	43.091
6.011	43.939
6.011	46.848
6.011	47.697
6.011	51.818
6.011	53.030
6.011	54.970
6.056	41.152
6.056	42.121
6.056	50.242
6.056	51.091
6.967	37.636
6.967	42.848
7.013	39.091
7.013	39.939
7.013	40.545
7.013	41.758
7.013	43.818
7.058	45.273
7.058	46.000
7.058	46.970
7.058	47.455
7.058	48.303
7.058	49.030
7.058	49.879
7.058	50.727
7.058	51.697
7.058	52.545
7.058	53.636
7.058	54.485
7.058	55.576
7.058	56.667
7.058	57.636
7.104	34.848
7.923	41.030
7.923	41.515
7.969	40.061
8.015	42.606
8.015	55.818
8.015	56.667
8.015	57.636
8.060	43.697
8.060	45.030
8.060	45.879
8.060	46.848
8.060	47.576
8.060	48.303
8.060	48.788
8.060	49.394
8.060	50.121
8.060	50.970
8.060	51.697
8.060	52.667
8.060	53.273
8.060	53.758
8.060	54.970
8.060	58.970
8.925	43.091
8.971	43.939
9.062	42.000
9.062	44.667
9.062	45.758
9.062	46.485
9.062	47.697
9.062	49.030
9.062	50.121
9.062	50.727
9.062	54.848
9.062	56.061
9.062	57.030
9.062	57.879
9.062	59.091
9.107	54.000
9.153	51.697
9.153	53.030
9.973	43.091
9.973	43.818
9.973	44.545
9.973	55.576
9.973	56.909
9.973	57.879
9.973	58.727
9.973	59.455
9.973	60.667
10.018	50.727
10.018	51.455
10.018	52.303
10.018	53.152
10.064	45.879
10.064	46.485
10.064	47.212
10.064	47.818
10.064	48.667
10.064	49.515
10.064	54.848
10.109	53.758
10.155	62.848
10.929	43.091
11.020	56.788
11.020	57.636
11.020	58.606
11.020	60.909
11.066	46.000
11.066	46.848
11.066	47.697
11.066	48.545
11.066	49.758
11.066	50.970
11.066	52.061
11.066	52.909
11.066	53.636
11.066	54.364
11.066	55.576
11.066	59.939
11.066	62.848
11.794	41.758
11.976	47.939
11.976	48.667
11.976	49.636
11.976	61.030
11.976	62.364
11.976	63.576
12.022	50.848
12.022	51.697
12.022	52.667
12.022	53.636
12.022	54.606
12.022	55.576
12.022	56.545
12.022	57.636
12.022	58.727
12.022	59.939
12.933	44.788
12.933	58.121
12.933	59.091
12.978	47.818
12.978	48.788
12.978	49.636
12.978	51.576
12.978	52.667
12.978	53.636
12.978	57.030
13.024	46.848
13.024	50.606
13.024	54.606
13.024	55.576
13.024	56.182
13.024	60.909
13.024	61.636
13.024	62.848
13.069	60.061
13.934	62.485
13.980	50.848
13.980	51.697
13.980	52.909
13.980	53.758
13.980	61.515
13.980	63.818
14.026	49.758
14.026	54.606
14.026	55.576
14.026	56.424
14.026	57.273
14.026	58.606
14.026	59.455
14.026	60.424
14.071	48.909
14.071	58.000
14.982	52.182
14.982	52.909
14.982	61.758
14.982	62.727
14.982	63.818
14.982	64.667
15.027	50.121
15.027	53.636
15.027	54.848
15.027	57.152
15.027	58.970
15.027	59.939
15.027	60.667
15.073	46.970
15.073	56.061
15.073	58.000
15.118	44.061
15.984	51.091
15.984	51.939
15.984	52.788
15.984	55.939
15.984	56.667
15.984	57.515
15.984	58.242
15.984	59.455
15.984	60.424
15.984	64.788
16.029	53.879
16.029	54.848
16.029	61.515
16.029	63.455
16.940	48.788
16.940	66.000
16.985	60.909
16.985	61.636
16.985	63.212
16.985	63.818
17.031	50.242
17.031	51.212
17.031	57.515
17.031	58.242
17.031	58.727
17.031	59.455
17.031	59.939
17.077	52.061
17.077	52.909
17.077	53.636
17.077	54.606
17.077	55.576
17.077	56.545
17.896	58.242
17.942	59.212
17.987	49.879
17.987	51.455
17.987	52.788
17.987	53.879
17.987	54.727
17.987	56.909
17.987	61.515
17.987	62.485
17.987	63.576
17.987	64.061
17.987	65.030
17.987	66.485
18.033	55.697
18.033	59.818
18.033	60.545
18.078	69.758
18.944	50.970
18.944	66.121
18.944	66.848
18.989	52.788
19.035	56.667
19.035	58.000
19.035	61.879
19.035	62.727
19.035	63.818
19.080	53.879
19.080	54.606
19.080	56.061
19.080	59.091
19.080	59.818
19.080	60.788
19.080	69.152
19.171	41.152
19.991	52.909
19.991	53.879
19.991	54.848
19.991	55.818
20.036	56.667
20.036	57.879
20.036	59.091
20.036	59.818
20.036	60.788
20.036	61.636
20.036	62.848
20.036	63.939
20.947	58.485
20.947	58.970
20.947	60.061
20.993	57.030
20.993	62.848
20.993	63.697
20.993	66.727
21.038	51.818
21.038	56.061
21.038	65.879
21.084	60.909
21.084	61.879
21.084	64.424
21.995	56.788
21.995	57.515
22.040	60.424
22.086	56.061
22.086	58.970
22.086	59.818
22.086	61.879
22.086	62.848
22.086	63.455
22.086	64.303
22.086	65.030
22.086	65.879
22.086	66.970
22.131	58.242
22.905	58.727
22.905	60.667
22.905	61.394
22.996	62.606
22.996	64.303
22.996	65.273
23.042	54.848
23.042	63.333
23.042	66.121
23.087	53.879
23.953	59.818
23.953	61.515
23.953	66.970
23.998	58.970
23.998	65.030
23.998	66.242
23.998	70.727
24.044	63.212
24.044	64.182
24.135	57.273
25.091	60.182
25.091	61.879
26.093	65.273];
data.tL_f(:,1) = 365 * (.5 + data.tL_f(:,1)); % convert yr to d
n=size(data.tL_f,1); for i=2:n; if data.tL_f(i,1)<=data.tL_f(i-1,1); data.tL_f(i,1)=data.tL_f(i-1,1)+1e-3; end; end
units.tL_f = {'d', 'cm'}; label.tL_f = {'time since birth', 'total length', 'female'};  
temp.tL_f = C2K(6);  units.temp.tL_f = 'K'; label.temp.tL_f = 'temperature';
bibkey.tL_f = 'ContArel2014';
comment.tL_f = 'data for females';
%
data.tL_m = [ ... % year class (yr), total length (cm)
0.912	25.700
0.953	26.795
0.982	45.172
0.996	24.604
1.000	19.858
1.075	32.028
1.081	23.266
1.082	21.805
1.945	49.919
1.957	32.394
1.961	27.647
1.993	42.252
1.993	41.156
1.997	35.801
2.001	30.446
2.001	29.473
2.004	26.552
2.004	25.700
2.005	24.848
2.005	23.874
2.006	22.657
2.007	21.805
2.023	58.073
2.041	33.611
2.084	31.420
2.086	28.986
2.956	45.781
2.957	44.564
2.958	43.712
2.958	42.982
2.959	41.765
2.960	40.548
2.961	39.331
2.961	38.600
2.962	37.748
2.963	37.018
2.963	36.410
2.964	34.341
2.965	33.732
2.965	33.124
2.966	32.272
2.967	30.690
2.971	24.970
3.006	35.680
3.010	29.594
3.011	27.647
3.012	27.039
3.052	28.864
3.924	44.807
3.924	43.834
3.924	43.469
3.925	42.738
3.927	39.574
3.928	38.722
3.965	45.781
3.968	41.643
3.968	40.913
3.975	31.907
3.975	31.055
3.976	30.203
3.977	29.108
4.004	50.284
4.005	48.702
4.006	46.633
4.012	37.992
4.014	35.680
4.015	34.828
4.015	34.097
4.016	33.124
4.048	47.728
4.053	40.426
4.055	37.383
4.055	36.775
4.929	49.432
4.931	45.538
4.973	46.755
4.973	46.268
5.013	48.945
5.013	48.580
5.014	47.606
5.016	44.442
5.017	43.347
5.018	42.495
5.018	41.765
5.019	41.034
5.019	40.426
5.019	39.817
5.020	38.722
5.021	37.748
5.021	37.018
5.022	35.801
5.023	34.828
5.024	33.854
5.062	39.452
5.066	33.002
5.939	46.389
5.940	45.659
5.946	36.775
5.947	35.801
5.990	33.732
6.019	51.866
6.020	50.527
6.021	49.919
6.022	48.458
6.022	47.485
6.025	44.442
6.025	43.469
6.026	42.982
6.026	42.008
6.027	40.548
6.028	39.574
6.028	39.087
6.029	37.870
6.032	34.584
6.069	41.521
6.910	39.817
6.944	51.988
6.984	53.935
6.986	51.501
6.987	50.771
6.987	49.432
6.988	48.824
6.988	48.215
6.989	47.120
6.993	41.765
6.994	40.669
6.995	38.844
6.996	37.992
7.027	53.205
7.032	46.511
7.032	45.538
7.033	44.686
7.033	44.077
7.034	43.103
7.952	51.501
7.953	50.892
7.961	39.209
7.962	38.357
7.992	54.787
7.994	52.596
7.996	49.919
7.996	48.945
7.999	45.172
8.002	40.548
8.002	40.061
8.033	56.004
8.034	54.422
8.035	53.327
8.039	47.972
8.039	47.485
8.040	46.998
8.040	46.511
8.040	45.903
8.042	44.077
8.042	43.347
8.043	42.617
8.043	41.765
8.865	68.905
8.922	46.998
8.965	45.659
8.967	42.617
8.968	41.643
8.969	39.939
9.008	44.686
9.041	57.586
9.042	55.761
9.043	54.787
9.043	53.935
9.044	52.840
9.045	51.866
9.045	51.258
9.045	51.136
9.046	50.406
9.046	49.675
9.047	48.945
9.047	48.093
9.050	43.712
9.892	41.156
9.931	45.781
9.935	39.939
9.970	49.919
9.971	49.067
9.971	48.458
9.972	47.606
9.975	42.860
9.976	42.008
10.006	58.682
10.007	57.708
10.007	56.978
10.008	56.369
10.008	55.517
10.009	54.909
10.009	54.057
10.010	53.570
10.011	52.475
10.011	51.744
10.012	51.014
10.015	46.755
10.016	44.807
10.017	43.712
10.895	49.432
10.896	48.702
10.934	53.448
10.935	52.475
10.939	46.268
10.941	43.955
10.973	58.316
10.973	57.708
10.977	51.744
10.978	50.649
10.980	47.972
10.981	47.241
10.982	44.929
10.986	39.939
11.016	56.978
11.017	55.639
11.017	54.909
11.018	54.179
11.026	42.982
11.935	64.158
11.946	48.337
11.947	47.606
11.980	59.899
11.981	58.925
11.982	57.951
11.986	51.744
11.986	51.136
11.987	50.284
11.988	48.945
11.989	46.755
12.024	56.978
12.025	56.247
12.026	54.909
12.026	53.935
12.027	53.327
12.027	52.596
12.074	45.538
12.075	44.929
12.075	44.077
12.915	45.416
12.916	44.199
12.947	59.655
12.947	58.803
12.948	58.195
12.948	57.343
12.949	56.978
12.949	56.247
12.985	64.402
12.992	55.030
12.992	54.300
12.994	52.475
12.994	51.866
12.995	51.014
12.995	50.284
12.996	48.824
12.997	48.093
13.035	53.327
13.038	49.554
13.082	46.633
13.914	58.438
13.922	46.511
13.923	45.781
13.923	45.051
13.958	54.909
13.963	48.702
13.963	47.850
13.964	47.120
13.996	60.872
13.997	59.655
13.999	57.708
13.999	56.734
14.000	55.761
14.001	54.422
14.001	53.448
14.002	53.205
14.002	52.475
14.003	51.744
14.003	50.892
14.046	50.162
14.046	49.554
14.878	61.968
14.879	60.142
14.880	59.047
14.890	44.929
14.891	43.712
14.919	62.698
14.923	58.073
14.923	57.099
14.926	53.570
14.926	52.840
14.927	51.866
14.928	50.771
14.928	49.797
14.929	48.580
14.930	47.850
14.930	46.998
14.966	56.369
14.966	55.761
14.967	55.274
14.967	54.422
14.975	43.103
15.937	50.162
15.939	46.998
15.970	62.698
15.971	60.751
15.972	59.899
15.972	59.047
15.973	58.073
15.974	56.734
15.975	55.761
15.975	54.787
15.976	53.813
15.976	53.327
15.977	52.353
15.978	51.379
16.021	49.310
16.022	48.215
16.939	59.290
16.939	58.682
16.940	57.830
16.940	56.734
16.941	55.639
16.942	54.422
16.942	53.935
16.945	49.797
16.946	48.945
16.985	52.718
16.986	51.866
16.986	50.892
17.021	61.116
17.022	60.629
17.902	63.063
17.945	62.211
17.948	57.343
17.949	56.734
17.949	56.126
17.988	61.359
17.988	60.629
17.989	59.655
17.989	58.682
17.992	55.517
17.992	54.787
17.993	53.935
17.993	52.961
17.994	52.596
17.995	50.649
17.996	49.675
17.996	48.945
17.997	48.093
17.998	46.998
18.032	58.073
18.036	51.623
18.877	51.744
18.916	55.761
18.918	52.353
18.920	49.675
18.952	64.767
18.952	63.671
18.954	61.846
18.954	61.116
18.954	60.629
18.955	59.655
18.955	59.168
18.956	58.682
18.956	58.195
18.957	57.586
18.957	56.491
18.959	54.665
18.959	54.057
18.960	53.205
18.962	50.527
18.963	48.580
19.882	55.761
19.925	54.544
19.926	53.083
19.927	52.231
19.927	51.136
19.962	61.724
19.963	60.872
19.964	59.655
19.964	58.682
19.965	58.195
19.965	57.465
19.966	56.613
20.056	47.120
20.970	63.063
20.970	62.089
20.971	60.872
20.972	59.655
20.973	58.682
20.973	57.951
20.974	57.221
20.975	55.882
20.975	54.787
20.976	53.692
20.977	52.961
20.977	52.353
21.104	51.014
21.940	56.613
21.978	62.576
21.980	60.751
21.981	59.047
21.982	57.830
21.982	57.221
21.983	55.639
21.984	54.179
21.986	52.110
22.022	60.020
22.061	65.010
22.907	56.491
22.946	60.020
22.947	58.925
22.950	55.396
22.986	63.915
22.987	62.089
22.990	57.708
22.992	54.300
23.957	57.586
24.000	55.761];
data.tL_m(:,1) = 365 * (.5 + data.tL_m(:,1)); % convert yr to d
n=size(data.tL_m,1); for i=2:n; if data.tL_m(i,1)<=data.tL_m(i-1,1); data.tL_m(i,1)=data.tL_m(i-1,1)+1e-3; end; end
units.tL_m = {'d', 'cm'}; label.tL_m = {'time since birth', 'total length', 'male'};  
temp.tL_m = C2K(6);  units.temp.tL_m = 'K'; label.temp.tL_m = 'temperature';
bibkey.tL_m = 'ContArel2014';
comment.tL_m = 'data for males';

%% set weights for all real data
weights = setweights(data, []);
weights.tL_f = 5 * weights.tL_f;
weights.tL_m = 5 * weights.tL_m;
weights.Li = 5 * weights.Li;

%% set pseudodata and respective weights
[data, units, label, weights] = addpseudodata(data, units, label, weights);
weights.psd.v = 5 * weights.psd.v;

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

%% Group plots
set1 = {'tL_f','tL_m'}; subtitle1 = {'Data for females, males'};
metaData.grp.sets = {set1};
metaData.grp.subtitle = {subtitle1};

%% Discussion
D1 = 'males are assumed to differ from females by {p_Am} only';
D2 = 'mod_1: males have equal state variables at b, compared to females';
metaData.discussion = struct('D1',D1, 'D2',D2);  

%% Facts
F1 = 'length-weight: Ww in g = 0.00355*(TL in cm)^3.16';
metaData.bibkey.F1 = 'fishbase'; 
F2 = 'Marine; benthopelagic; oceanodromous';
metaData.bibkey.F2 = 'fishbase'; 
metaData.facts = struct('F1',F1,'F2',F2);

%% Links
metaData.links.id_CoL = '42Z4S'; % Cat of Life
metaData.links.id_ITIS = '164775'; % ITIS
metaData.links.id_EoL = '46564425'; % Ency of Life
metaData.links.id_Wiki = 'Micromesistius_australis'; % Wikipedia
metaData.links.id_ADW = 'Micromesistius_australis'; % ADW
metaData.links.id_Taxo = '44337'; % Taxonomicon
metaData.links.id_WoRMS = '234781'; % WoRMS
metaData.links.id_fishbase = 'Micromesistius-australis'; % fishbase


%% References
bibkey = 'Wiki'; type = 'Misc'; bib = ...
'howpublished = {\url{https://en.wikipedia.org/wiki/Micromesistius_australis}}';
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 = 'ContArel2014'; type = 'article'; bib = [ ...
'author = {Javier E. Contreras-Reyes and Reinaldo B. Arellano-Valle and T. Mariella Canales}, ' ... 
'year   = {2014}, ' ...
'title  = {Comparing growth curves with asymmetric heavy-tailed errors: {A}pplication to the southern blue whiting (\emph{Micromesistius australis})}, ' ...
'journal = {Fisheries Research}, ' ...
'page = {88-94}, ' ...
'volume = {159}'];
metaData.biblist.(bibkey) = ['''@', type, '{', bibkey, ', ' bib, '}'';'];
%
bibkey = 'fishbase'; type = 'Misc'; bib = ...
'howpublished = {\url{http://www.fishbase.org/summary/Micromesistius-australis.html}}';
metaData.biblist.(bibkey) = ['''@', type, '{', bibkey, ', ' bib, '}'';'];

