cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30334252.v4
title: The Bayero University Kano (BUK) 2025/2026 1st And 2nd Batch Admission List Is Out Now Call Admin Office Call 09024168245, (09024168245) To Check And Further Admission Assistance Call +2349024168245.

description: The Bayero University Kano (BUK) 2025/2026 1st And 2nd Batch Admission List Is Out Now Call Admin Office Call 09024168245, (09024168245) To Check And Further Admission Assistance Call +2349024168245.
DOI: 10.25346/s6eecgix/ytgtei
title: msXL_344v_46_27.tif
DOI: 10.25346/s6eecgix/q3cwhk
title: msXL_344v_46_26.tif
DOI: 10.25346/s6eecgix/gtndiw
title: msXL_344v_46_25.tif
DOI: 10.25346/s6eecgix/9jlzby
title: msXL_344v_31_24.tif
DOI: 10.25346/s6eecgix/8xfwxz
title: msXL_344v_31_23.tif
DOI: 10.25346/s6eecgix/yuklt2
title: msXL_344v_31_22.tif
DOI: 10.25346/s6eecgix/5kdzwk
title: msXL_344v_31_21.tif
DOI: 10.5281/zenodo.17316787
title: CoCiP and APCEMM Raw Outputs
DOI: 10.5281/zenodo.17316788
title: CoCiP and APCEMM Raw Outputs
DOI: 10.25346/s6eecgix/vyfm8o
title: msXL_344v_31_20.tif
DOI: 10.25346/s6eecgix/wigasg
title: msXL_344v_31_19.tif
DOI: 10.15468/dl.ztk6rt
title: Occurrence Download

description: A dataset containing 6349 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Switzerland",
 "OccurrenceStatus is Present",
 "PublishingOrg is 64ee55c9-570a-42af-b7da-3f13c6b4e5a9",
 "TaxonKey is Pieris mannii (Mayer, 1851)"
 ]
}

 The dataset includes 6349 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056541-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25625/qutuwu/0tdifu
title: p10_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/184ue4
title: wytham_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/2cib1v
title: p2.laz

description: :unav
DOI: 10.25625/qutuwu/df56fb
title: p12_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/eztdsr
title: p1.laz

description: :unav
DOI: 10.25625/qutuwu/jk0sur
title: p14_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/mzklly
title: p12.laz

description: :unav
DOI: 10.25625/qutuwu/qvqqnw
title: wytham.laz

description: :unav
DOI: 10.25625/qutuwu/wqocro
title: p1_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/xouwp4
title: p2_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/yhfl2j
title: p14.laz

description: :unav
DOI: 10.25625/qutuwu/1qawes
title: p12.laz

description: :unav
DOI: 10.25625/qutuwu/2y1dvf
title: p2.laz

description: :unav
DOI: 10.25625/qutuwu/3bfg4w
title: p4.laz

description: :unav
DOI: 10.25625/qutuwu/4mihv1
title: p12_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/cgcwpr
title: p10.laz

description: :unav
DOI: 10.25625/qutuwu/dcbull
title: p1.laz

description: :unav
DOI: 10.25625/qutuwu/fcixgi
title: p1_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/glmzqb
title: open_files.ipynb

description: :unav
DOI: 10.25625/qutuwu/gpa9f4
title: p14_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/hzueow
title: p10.laz

description: :unav
DOI: 10.25625/qutuwu/riulzl
title: p14.laz

description: :unav
DOI: 10.25625/qutuwu/rzsqmq
title: p10_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/x6lhwb
title: p4.laz

description: :unav
DOI: 10.25625/qutuwu/z92c8e
title: p4_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu
title: Extended version of WYTHAM and LAUTx

description: Note: To better find the files to download, select "Change View: Tree". This dataset is associated with the paper "TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds" published in Ecological Informatics and the ML4RS workshop paper "Towards general deep-learning-based tree instance segmentation models" presented at ICLR 2024. It extends the publicly available segmented tree data that was introduced by Calders et al. [1] and Tockner et al. [2]. These two publications only provide segmented trees. For this dataset, these tree labels were propagated to the original point clouds and the remaining points were automatically classified as either "non-tree points" or "unlabeled". Furthermore, some manual correction of the segmented trees was conducted, especially for the tree bases in Tockner et al. [2]. A more comprehensive description of the dataset is given in the linked publications. We provide the laser scans in the original resolution as well as in a voxelized form where the point cloud has been subsampled to contain only one point within a cube with edge length 0.1m. We provide the forest laser scans in the .laz format and follow the same labeling scheme proposed by Puliti et al. [3]. Specifically, a unique identifier is stored as an additional field named "treeID" in the .laz files. Trees are labeled starting from 1 and all non-tree points have the label 0 in the treeID field. The dataset comes with a classification into the three semantic categories "non-tree-points" (label=2), "unlabeled" (label=3) and "tree-points" (label=4) that is saved in the classification field of the .laz file. The .laz format is compatible with popular point cloud processing tools like CloudCompare and can also be loaded in python using the laspy package. Example code for opening .laz files in python as numpy arrays is provided in the open_files.ipynb notebook. References [1] Calders, K., Origo, N., Burt, A., Disney, M., Nightingale, J., Raumonen, P., ... & Lewis, P. (2018). Realistic forest stand reconstruction from terrestrial LiDAR for radiative transfer modelling. Remote Sensing, 10(6), 933. [2] Tockner, A., Gollob, C., Kraßnitzer, R., Ritter, T., & Nothdurft, A. (2022). Automatic tree crown segmentation using dense forest point clouds from Personal Laser Scanning (PLS). International Journal of Applied Earth Observation and Geoinformation, 114, 103025. [3] Puliti, S., Pearse, G., Surový, P., Wallace, L., Hollaus, M., Wielgosz, M., & Astrup, R. (2023). FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees. arXiv preprint arXiv:2309.01279.
DOI: 10.25625/qutuwu/dmcifj
title: wytham.laz

description: :unav
DOI: 10.25625/qutuwu/ojg4x8
title: p2_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/xhcrg5
title: p4_vox0.1.laz

description: :unav
DOI: 10.25625/qutuwu/zmnena
title: wytham_vox0.1.laz

description: :unav
DOI: 10.25625/vpmpid/2kl2w6
title: LG1.npz

description: :unav
DOI: 10.25625/vpmpid/f1lfv1
title: LG3.npz

description: :unav
DOI: 10.25625/vpmpid/6puxjx
title: L2N.npz

description: :unav
DOI: 10.25625/vpmpid/7wwgqn
title: G1W.npz

description: :unav
DOI: 10.25625/vpmpid/8isojq
title: L1W.npz

description: :unav
DOI: 10.25625/vpmpid/9qbpik
title: _las_L1W.zip

description: :unav
DOI: 10.25625/vpmpid/arbsn6
title: G2N.npz

description: :unav
DOI: 10.25625/vpmpid/fin2nn
title: G4W.npz

description: :unav
DOI: 10.25625/vpmpid/gzxxuj
title: L2W.npz

description: :unav
DOI: 10.25625/vpmpid/humkwy
title: O1W.npz

description: :unav
DOI: 10.25625/vpmpid/lszakn
title: A1N.npz

description: :unav
DOI: 10.25625/vpmpid/obwzm7
title: G2W.npz

description: :unav
DOI: 10.25625/vpmpid/psb6su
title: ReadMe.txt

description: :unav
DOI: 10.25625/vpmpid/0hkpxl
title: G3W.npz

description: :unav
DOI: 10.25625/vpmpid/16fd31
title: LG2.npz

description: :unav
DOI: 10.25625/vpmpid/83jwgl
title: L1N.npz

description: :unav
DOI: 10.25625/vpmpid/conpa6
title: O1N.npz

description: :unav
DOI: 10.25625/vpmpid/jhj2en
title: L1W_voxelized01.npz

description: :unav
DOI: 10.25625/vpmpid/l12gkr
title: A1W.npz

description: :unav
DOI: 10.25625/vpmpid/mrzyk7
title: G3N.npz

description: :unav
DOI: 10.25625/vpmpid/nhkxi5
title: G1N.npz

description: :unav
DOI: 10.25625/vpmpid/wya6q3
title: G4N.npz

description: :unav
DOI: 10.25625/vpmpid/yvv2ox
title: _las_automatically_segmented_data.zip

description: :unav
DOI: 10.25625/vpmpid/4ba1bd
title: A1W.laz

description: :unav
DOI: 10.25625/vpmpid/67holf
title: checkpoint_classifier.pth

description: :unav
DOI: 10.25625/vpmpid/8a0mqc
title: checkpoint_classifier.pth

description: :unav
DOI: 10.25625/vpmpid/e8y1iv
title: finetuned_checkpoint_classifier.pth

description: :unav
DOI: 10.25625/vpmpid/je6koc
title: open_files.ipynb

description: :unav
DOI: 10.25625/vpmpid/jtjreo
title: finetuned_checkpoint_classifier.pth

description: :unav
DOI: 10.25625/vpmpid/jtpzrg
title: finetuned_checkpoint_pointwise_prediction.pth

description: :unav
DOI: 10.25625/vpmpid/mofuyc
title: G1N.laz

description: :unav
DOI: 10.25625/vpmpid/ugaqtv
title: evaluated_trees.txt

description: :unav
DOI: 10.25625/vpmpid/vz2enj
title: A1N.laz

description: :unav
DOI: 10.25625/vpmpid/wfjlnw
title: checkpoint_pointwise_prediction.pth

description: :unav
DOI: 10.25625/vpmpid/0fiqfd
title: G4N.laz

description: :unav
DOI: 10.25625/vpmpid/2ou297
title: L2N.laz

description: :unav
DOI: 10.25625/vpmpid/8zolyb
title: L1N.laz

description: :unav
DOI: 10.25625/vpmpid/gqaigp
title: G2N.laz

description: :unav
DOI: 10.25625/vpmpid/i0m17s
title: G1W.laz

description: :unav
DOI: 10.25625/vpmpid/k8uopu
title: G3N.laz

description: :unav
DOI: 10.25625/vpmpid/kt8eb4
title: G3W.laz

description: :unav
DOI: 10.25625/vpmpid/uxbeds
title: O1N.laz

description: :unav
DOI: 10.25625/vpmpid/xhacrg
title: G2W.laz

description: :unav
DOI: 10.25625/vpmpid/xxws3z
title: G4W.laz

description: :unav
DOI: 10.25625/vpmpid/ygjklj
title: L2W.laz

description: :unav
DOI: 10.25625/vpmpid/0wdxl6
title: plot7_cut.laz

description: :unav
DOI: 10.25625/vpmpid/1ie8cp
title: O1W.laz

description: :unav
DOI: 10.25625/vpmpid/1jmeqv
title: model_weights_diverse_training_data.pth

description: :unav
DOI: 10.25625/vpmpid/3wba7s
title: LG1.laz

description: :unav
DOI: 10.25625/vpmpid/8ciiw0
title: model_weights_finetuned.pth

description: :unav
DOI: 10.25625/vpmpid/aqm6vo
title: L1W_voxelized01.laz

description: :unav
DOI: 10.25625/vpmpid/hohsib
title: open_files.ipynb

description: :unav
DOI: 10.25625/vpmpid/m4tgl7
title: model_weights_dirty.pth

description: :unav
DOI: 10.25625/vpmpid/qxxj2i
title: L1W.laz

description: :unav
DOI: 10.25625/vpmpid/tduf3s
title: ReadMe.txt

description: :unav
DOI: 10.25625/vpmpid/1k7mcr
title: L1W_voxelized01.laz

description: :unav
DOI: 10.25625/vpmpid/65q3nw
title: L1W_voxelized01_for_eval.laz

description: :unav
DOI: 10.25625/vpmpid/c1ahqw
title: model_weights_diverse_training_data.pth

description: :unav
DOI: 10.25625/vpmpid/edg9ib
title: LG3.laz

description: :unav
DOI: 10.25625/vpmpid/gokv7w
title: L1W_voxelized01_for_eval.laz

description: :unav
DOI: 10.25625/vpmpid/imhf3g
title: model_weights_20241213.pth

description: :unav
DOI: 10.25625/vpmpid/objtig
title: LG2.laz

description: :unav
DOI: 10.25625/vpmpid/qcy3zl
title: ReadMe.txt

description: :unav
DOI: 10.25625/vpmpid/tyzj4e
title: model_weights_with_small_20241213.pth

description: :unav
DOI: 10.25625/vpmpid/wtib7f
title: evaluated_trees.txt

description: :unav
DOI: 10.25625/vpmpid/zitxoq
title: L1W.laz

description: :unav
DOI: 10.15468/dl.v6skpu
title: Occurrence Download

description: A dataset containing 88649 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Delphinus delphis Linnaeus, 1758",
 "Year 2000-2025"
 ]
}

 The dataset includes 88649 records from 388 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056543-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14598874
title: CubeSat Image Classify Hackathon dataset
DOI: 10.5281/zenodo.14598875
title: CubeSat Image Classify Hackathon dataset
DOI: 10.15468/dl.47uyj9
title: Occurrence Download

description: A dataset containing 331 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((80 0,165 0,165 60,80 60,80 0))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ulmus davidiana var. japonica (Rehder) Nakai",
 "Year 2000-2025"
 ]
}

 The dataset includes 331 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056544-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rg3qhx
title: Occurrence Download

description: A dataset containing 28651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Switzerland",
 "OccurrenceStatus is Present",
 "PublishingOrg is 64ee55c9-570a-42af-b7da-3f13c6b4e5a9",
 "TaxonKey is Aglais io (Linnaeus, 1758)"
 ]
}

 The dataset includes 28651 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056545-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27239001
title: Meta Dataset

description: Underlying data and CONSORT checklist for assessing effectiveness of Helfer skin Tap Technique on Pain among Infants undergoing Intramuscular Vaccination – A Randomized Controlled Trial.This RCT study examined the difference in pain score between groups receiving the following interventions: (1) Standard injection technique (2) Helfer skin tap technique. For this, a post-test control design was adopted.
DOI: 10.6084/m9.figshare.27239001.v1
title: Meta Dataset

description: “Effectiveness of Helfer skin Tap Technique on Pain among Infants undergoing Intramuscular Vaccination – A Randomized Controlled Trial”This RCT study examined the difference in pain score between groups receiving the following interventions: (1) Standard injection technique (2) Helfer skin tap technique. For this, a post-test control design was adopted.
DOI: 10.15468/dl.5zhzs9
title: Occurrence Download

description: A dataset containing 4457 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Equus caballus Linnaeus, 1758",
 "Country is United States of America",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 4457 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056546-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14597774
title: 【outputs_best_number_tokens_to_tpm_large_scales】/best_number_tokens_log_part_19 (5), only two 70B LLMs, 100 (tpms) = 100 files

description: Part 19 (5)  

only two 70B LLMs,  

only valid results (both MP p value and CI),

all permutation controls,

all seeds,

all linguistic spans,

all 5 tasks, 

100 (tpms) = 100 files
DOI: 10.5281/zenodo.14597775
title: 【outputs_best_number_tokens_to_tpm_large_scales】/best_number_tokens_log_part_19 (5), only two 70B LLMs, 100 (tpms) = 100 files

description: Part 19 (5)  

only two 70B LLMs,  

only valid results (both MP p value and CI),

all permutation controls,

all seeds,

all linguistic spans,

all 5 tasks, 

100 (tpms) = 100 files
DOI: 10.15468/dl.b4jjwk
title: Occurrence Download

description: A dataset containing 2719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Anartia amathea (Linnaeus, 1758)"
 ]
}

 The dataset includes 2719 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056548-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28137713
title: Data for Figure 2

description: *Data for Fig. 2 in the main text (symbol rate Rsym = 0.5 MHz)*File name format: Fig2_PxxBm_Rsym0p5MHz, where xx is the drive power in dBm.Column#1: drive frequency (Hz)Column#2: measured epsilon, reciprocal of error vector magnitude (dB)Column#3: calculated epsilon (dB)Column#4: measured L, IQ vector length in one quadrant of the constellation diagram (mV)Column#5: calculated L (mV)Column#6: calculated Bit Error Ratio (unitless, since it is a ratio)Column#7: calculated Bit Error Ratio with symbol clouds rotated so they are confined to their quadrants (unitless)
DOI: 10.6084/m9.figshare.28137713.v1
title: Data for Figure 2

description: *Data for Fig. 2 in the main text (symbol rate Rsym = 0.5 MHz)*File name format: Fig2_PxxBm_Rsym0p5MHz, where xx is the drive power in dBm.Column#1: drive frequency (Hz)Column#2: measured epsilon, reciprocal of error vector magnitude (dB)Column#3: calculated epsilon (dB)Column#4: measured L, IQ vector length in one quadrant of the constellation diagram (mV)Column#5: calculated L (mV)Column#6: calculated Bit Error Ratio (unitless, since it is a ratio)Column#7: calculated Bit Error Ratio with symbol clouds rotated so they are confined to their quadrants (unitless)
DOI: 10.6084/m9.figshare.28137719
title: data.zip

description: This is the raw data related by a manuscript
DOI: 10.6084/m9.figshare.28137722
title: Figure 2B source data.xlsx

description: the codelibrary(ggplot2)library(readxl)library(dplyr)library(tidyr)library(gridExtra)library(ggpubr)data_long &lt;- data %&gt;% pivot_longer(cols = starts_with("value"), names_to = "measurement", values_to = "value")comparison_list &lt;- list(c("Control", "Heat stress"))plot_list &lt;- lapply(unique(data_long$sample), function(sample) { df &lt;- data_long %&gt;% filter(sample == !!sample) ggplot(df, aes(x = group, y = value, color = group, fill = group)) + geom_jitter(width = 0.15) + geom_boxplot(width = 0.4, alpha = 0.2) + scale_color_manual(values = c("#6F99AD", "#BF5960")) + scale_fill_manual(values = c("#6F99AD", "#BF5960")) + theme_test() + stat_compare_means(comparisons = comparison_list, method = "t.test", label = "p.signif") + labs(title = sample, y = sample, x = "") + scale_y_continuous(expand = expansion(c(0.1, 0.1))) + theme(axis.text = element_text(color = "black", size = 10), axis.line = element_blank(), legend.position = "none")})grid.arrange(grobs = plot_list, nrow = 2, ncol = 4)
DOI: 10.6084/m9.figshare.28137722.v1
title: Figure 2B source data.xlsx

description: the codelibrary(ggplot2)library(readxl)library(dplyr)library(tidyr)library(gridExtra)library(ggpubr)data_long &lt;- data %&gt;% pivot_longer(cols = starts_with("value"), names_to = "measurement", values_to = "value")comparison_list &lt;- list(c("Control", "Heat stress"))plot_list &lt;- lapply(unique(data_long$sample), function(sample) { df &lt;- data_long %&gt;% filter(sample == !!sample) ggplot(df, aes(x = group, y = value, color = group, fill = group)) + geom_jitter(width = 0.15) + geom_boxplot(width = 0.4, alpha = 0.2) + scale_color_manual(values = c("#6F99AD", "#BF5960")) + scale_fill_manual(values = c("#6F99AD", "#BF5960")) + theme_test() + stat_compare_means(comparisons = comparison_list, method = "t.test", label = "p.signif") + labs(title = sample, y = sample, x = "") + scale_y_continuous(expand = expansion(c(0.1, 0.1))) + theme(axis.text = element_text(color = "black", size = 10), axis.line = element_blank(), legend.position = "none")})grid.arrange(grobs = plot_list, nrow = 2, ncol = 4)
DOI: 10.15468/dl.wax9fr
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Sousa chinensis (Osbeck, 1765)",
 "Year 2000-2025"
 ]
}

 The dataset includes 289 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056549-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28137728
title: Nanomechanical Videos

description: Data for Figs 2, 3, 4, 5 in the manuscript entitled "A few-layer graphene nanomechanical resonator driven by digitally modulated video signals", by Ce Zhang, Heng Lu, Chen Yang, YuBin Zhang, FengNan Chen, Ying Yan, and Joel Moser.
DOI: 10.15468/dl.sbkrzr
title: Occurrence Download

description: A dataset containing 20616 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Chamaerops humilis L."
 ]
}

 The dataset includes 20616 records from 254 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056552-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fkh6kd
title: Occurrence Download

description: A dataset containing 1058312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((28.19258 49.87076,28.15125 50.29329,28.0057 50.70631,27.75691 51.09931,27.40883 51.46197,26.96852 51.78455,26.44622 52.05814,25.85521 52.27503,25.21151 52.42902,24.53332 52.51563,23.84031 52.53236,23.15281 52.47876,22.49087 52.35646,21.87339 52.1691,21.31736 51.92213,20.83724 51.62262,20.4446 51.27891,20.14785 50.90035,19.9523 50.49694,19.86026 50.07902,19.87127 49.65704,19.98242 49.24123,20.18865 48.84145,20.48305 48.46695,20.85722 48.12626,21.30146 47.82698,21.80504 47.57576,22.35643 47.37807,22.94344 47.23826,23.55345 47.15935,24.17352 47.14311,24.79058 47.18992,25.39155 47.29883,25.96355 47.46753,26.49401 47.69242,26.97091 47.96861,27.38289 48.29004,27.71956 48.64953,27.97165 49.03894,28.13136 49.44925,28.19258 49.87076)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 1058312 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056550-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.upp6g2
title: Occurrence Download

description: A dataset containing 99 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Cissia pseudoconfusa"
 ]
}

 The dataset includes 99 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056554-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uzerha
title: Occurrence Download

description: A dataset containing 21156 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stachys byzantina K.Koch"
 ]
}

 The dataset includes 21156 records from 328 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056553-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wccqqa
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Hamadryas amphinome mexicana (Lucas, 1853)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056555-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14599338
title: List of Marine Fish Species

description: List of marine fish species used in study entitled "Exploring artificial neural networks for the curation of DNA barcode reference libraries: a pilot study with marine fish species of the Eastern Atlantic and adjacent waters"
DOI: 10.5281/zenodo.14599339
title: List of Marine Fish Species

description: List of marine fish species used in study entitled "Exploring artificial neural networks for the curation of DNA barcode reference libraries: a pilot study with marine fish species of the Eastern Atlantic and adjacent waters"