cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24396/ordar-86
title: Table S4 - Magma-Mush Interactions in the Lower Oceanic crust: Insights from Atlantis Bank Layered Series (Southwest Indian Ridge)

description: In-situ trace element contents of plagioclase, clinopyroxene and olivine analyzed with a ThermoFinnigan Element2 XR ICP-MS coupled with a Microlas-GeoLas Q+ housing a Lambda-Physik CompEx 102 excimer laser at Géosciences Montpellier (AETE-ISO regional facility of the OSU OREME, Montpellier University, France). Signal acquisition was performed in time-resolved acquisition mode, counting 2 min for blanks and 1 min for sample measurements. The laser frequency was 8 Hz with an energy density of ~12–15 J•cm2. Ablation was performed in He gas, which was mixed with Ar before entering the plasma. Clinopyroxene (cpx) was analyzed with a laser spot size of 77 µm, whereas a spot size of 102 µm was used for ol (olivine) and pl (plagioclase). Data were processed using the GLITTER software (Van Achterberg et al., 2001). All measured concentrations were calibrated to the synthetic glass NIST 612 using the values of Pearce et al. (1997). Internal standards used for the minerals were 43Ca for cpx and 29Si for pl and ol, previously measured for each point by EPMA. The averaged values (and associated 2SD values) obtained by LA-ICP-MS analyses of the standard reference basalt BIR-1G are available at the end of Table S4, together with the average analytical errors for each element at the top.
DOI: 10.6084/m9.figshare.14095807
title: GRF_COP_AP_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095809
title: GRF_COP_AP_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095811
title: GRF_COP_AP_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095813
title: GRF_COP_AP_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095815
title: GRF_COP_ML_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095817
title: GRF_COP_ML_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095819
title: GRF_COP_ML_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095807.v1
title: GRF_COP_AP_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095809.v1
title: GRF_COP_AP_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095821
title: GRF_F_AP_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095811.v1
title: GRF_COP_AP_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095815.v1
title: GRF_COP_ML_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095813.v1
title: GRF_COP_AP_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095817.v1
title: GRF_COP_ML_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095823
title: GRF_COP_ML_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095827
title: GRF_F_AP_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095819.v1
title: GRF_COP_ML_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial.
DOI: 10.6084/m9.figshare.14095825
title: GRF_F_AP_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095829
title: GRF_F_ML_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095821.v1
title: GRF_F_AP_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095823.v1
title: GRF_COP_ML_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral COP signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095825.v1
title: GRF_F_AP_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095835
title: GRF_F_ML_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095827.v1
title: GRF_F_AP_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095829.v1
title: GRF_F_ML_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095831
title: GRF_F_AP_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095833.v1
title: GRF_F_ML_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095833
title: GRF_F_ML_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095837
title: GRF_F_V_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the vertical GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095839
title: GRF_F_V_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the vertical GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095831.v1
title: GRF_F_AP_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the anterior-posterior GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095835.v1
title: GRF_F_ML_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the medio-lateral GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095843
title: GRF_F_V_RAW_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the vertical GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095845
title: GRF_F_V_PRO_right

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the vertical GRF signals for each gait trial.
DOI: 10.6084/m9.figshare.14095837.v1
title: GRF_F_V_RAW_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the vertical GRF signals for each gait trial. Note that due to the non-normalized nature of the data and the resulting different time-series lengths in the “RAW” files, non-available numbers have been replaced by “NaN” to maintain a constant matrix-dimension.
DOI: 10.6084/m9.figshare.14095839.v1
title: GRF_F_V_PRO_left

description: The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third column each gait analysis session (“SESSION_ID”), and the fourth column each single gait trial within a session (“TRIAL_ID”). The remaining columns contain the values of the vertical GRF signals for each gait trial.