adsabs/AstroCLIMB huggingface dataset:
Paper: TREASUREHUNT: Transients and Variability Discovered with HST in the JWST North Ecliptic Pole Time-domain Field
Authors: Rosalia O'Brien, Rolf A. Jansen, Norman A. Grogin, Seth H. Cohen, Brent M. Smith, Ross M. Silver, W. P. Maksym, Rogier A. Windhorst, Timothy Carleton, Anton M. Koekemoer, Nimish P. Hathi, Christopher N. A. Willmer, Brenda L. Frye, M. Alpaslan, M. L. N. Ashby, T. A. Ashcraft, S. Bonoli, W. Brisken, N. Cappelluti, F. Civano, C. J. Conselice, V. S. Dhillon, S. P. Driver, K. J. Duncan, R. Dupke, M. Elvis, G. G. Fazio, S. L. Finkelstein, H. B. Gim, A. Griffiths, H. B. Hammel, M. Hyun, M. Im, V. R. Jones, D. Kim, B. Ladjelate, R. L. Larson, S. Malhotra, M. A. Marshall, S. N. Milam, J. D. R. Pierel, J. E. Rhoads, S. A. Rodney, H. J. A. Röttgering, M. J. Rutkowski, R. E. Ryan, M. J. Ward, C. W. White, R. J. van Weeren, X. Zhao, J. Summers, J. C. J. D'Silva, R. Ortiz, A. S. G. Robotham, D. Coe, M. Nonino, N. Pirzkal, H. Yan, T. Acharya
Figure caption: Star–galaxy separation, following Windhorst et al. (2011), using the SExtractor MAG_AUTO magnitudes in F606W vs. FWHM. Objects within gray regions, with FWHM < 0.″15 or m AB < 17 − 4 ﹩{\mathrm{log}}_{10}({\rm{FWHM}})﹩ mag, are flagged as stars and are not considered in this study. We also show the radius (0.″12) of the aperture used to identify variability as a vertical blue dashed line.
Paper: TREASUREHUNT: Transients and Variability Discovered with HST in the JWST North Ecliptic Pole Time-domain Field
Authors: Rosalia O'Brien, Rolf A. Jansen, Norman A. Grogin, Seth H. Cohen, Brent M. Smith, Ross M. Silver, W. P. Maksym, Rogier A. Windhorst, Timothy Carleton, Anton M. Koekemoer, Nimish P. Hathi, Christopher N. A. Willmer, Brenda L. Frye, M. Alpaslan, M. L. N. Ashby, T. A. Ashcraft, S. Bonoli, W. Brisken, N. Cappelluti, F. Civano, C. J. Conselice, V. S. Dhillon, S. P. Driver, K. J. Duncan, R. Dupke, M. Elvis, G. G. Fazio, S. L. Finkelstein, H. B. Gim, A. Griffiths, H. B. Hammel, M. Hyun, M. Im, V. R. Jones, D. Kim, B. Ladjelate, R. L. Larson, S. Malhotra, M. A. Marshall, S. N. Milam, J. D. R. Pierel, J. E. Rhoads, S. A. Rodney, H. J. A. Röttgering, M. J. Rutkowski, R. E. Ryan, M. J. Ward, C. W. White, R. J. van Weeren, X. Zhao, J. Summers, J. C. J. D'Silva, R. Ortiz, A. S. G. Robotham, D. Coe, M. Nonino, N. Pirzkal, H. Yan, T. Acharya
Figure caption: F606W images of each of the 12 transients identified within the JWST NEP TDF. For each transient we show a three-panel composite of 100 × 100 pixel (3″ × 3″) cutouts from the image in which the transient is present (left), the image in which the transient is absent (middle), and the difference image (right). Labels give the transient ID, the visit IDs and dates of observation, the time interval between epochs, and the apparent F606W magnitude of the transient. Transients T7, T10, and T11 were also detected in X-rays (see Table 3), with T7 and T10 likely quasars. Grayscale bars to the right of each three-panel set are in units of e − per second.
Paper: TREASUREHUNT: Transients and Variability Discovered with HST in the JWST North Ecliptic Pole Time-domain Field
Authors: Rosalia O'Brien, Rolf A. Jansen, Norman A. Grogin, Seth H. Cohen, Brent M. Smith, Ross M. Silver, W. P. Maksym, Rogier A. Windhorst, Timothy Carleton, Anton M. Koekemoer, Nimish P. Hathi, Christopher N. A. Willmer, Brenda L. Frye, M. Alpaslan, M. L. N. Ashby, T. A. Ashcraft, S. Bonoli, W. Brisken, N. Cappelluti, F. Civano, C. J. Conselice, V. S. Dhillon, S. P. Driver, K. J. Duncan, R. Dupke, M. Elvis, G. G. Fazio, S. L. Finkelstein, H. B. Gim, A. Griffiths, H. B. Hammel, M. Hyun, M. Im, V. R. Jones, D. Kim, B. Ladjelate, R. L. Larson, S. Malhotra, M. A. Marshall, S. N. Milam, J. D. R. Pierel, J. E. Rhoads, S. A. Rodney, H. J. A. Röttgering, M. J. Rutkowski, R. E. Ryan, M. J. Ward, C. W. White, R. J. van Weeren, X. Zhao, J. Summers, J. C. J. D'Silva, R. Ortiz, A. S. G. Robotham, D. Coe, M. Nonino, N. Pirzkal, H. Yan, T. Acharya
Figure caption: Histogram of the distribution of magnitude differences measured between two epochs (Δm 0.24) for all galaxies (4059 total) between 28.0 mag < m AB < 28.5 mag. The black circles show the number of galaxies (N) for each Δm 0.24 bin, where the error bar is ﹩\sqrt{N}﹩. The solid black curve is a Gaussian fit to the data. The vertical blue lines represent the 3σ thresholds based on the Gaussian fit. This proves that the distribution of Δm 0.24 follows a Gaussian distribution, such that the false detections can be assumed to follow Gaussian statistics (see Section 3.2.3).
Paper: TREASUREHUNT: Transients and Variability Discovered with HST in the JWST North Ecliptic Pole Time-domain Field
Authors: Rosalia O'Brien, Rolf A. Jansen, Norman A. Grogin, Seth H. Cohen, Brent M. Smith, Ross M. Silver, W. P. Maksym, Rogier A. Windhorst, Timothy Carleton, Anton M. Koekemoer, Nimish P. Hathi, Christopher N. A. Willmer, Brenda L. Frye, M. Alpaslan, M. L. N. Ashby, T. A. Ashcraft, S. Bonoli, W. Brisken, N. Cappelluti, F. Civano, C. J. Conselice, V. S. Dhillon, S. P. Driver, K. J. Duncan, R. Dupke, M. Elvis, G. G. Fazio, S. L. Finkelstein, H. B. Gim, A. Griffiths, H. B. Hammel, M. Hyun, M. Im, V. R. Jones, D. Kim, B. Ladjelate, R. L. Larson, S. Malhotra, M. A. Marshall, S. N. Milam, J. D. R. Pierel, J. E. Rhoads, S. A. Rodney, H. J. A. Röttgering, M. J. Rutkowski, R. E. Ryan, M. J. Ward, C. W. White, R. J. van Weeren, X. Zhao, J. Summers, J. C. J. D'Silva, R. Ortiz, A. S. G. Robotham, D. Coe, M. Nonino, N. Pirzkal, H. Yan, T. Acharya
Figure caption: SED fit of transient T4 with CIGALE, adopting the MMT/Binospec spectroscopic redshift of 0.615. The red points with vertical error bars show the measured fluxes of the transient host and their associated uncertainties. The horizontal bars on each data point represent the width of the bandpass. The light-gray spectrum represents the best CIGALE fit, with the reduced χ 2 value shown.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Histograms of observed absolute magnitudes for various subclasses of carbon stars. The vertical lines indicate theoretical magnitudes for CAGB models CA1 and CA7 (see Table 4). See Section 3.5.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Observed SEDs compared with more complex models (detached or double dust shell models): two CAGB stars in the upper panels with detached (O-rich) dust shell models and four other CAGB stars with double (C-rich and O-rich) dust shell models. See Section 5.2.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Period–color and period–magnitude relations for Mira variables in the CAGB sample. For each subclass, the number of objects is shown. The number in parenthesis denotes the number of objects plotted with good-quality observed data. See Section 7.1.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Observed SEDs compared with simple dust shell models: eight visual CAGB stars (visual-CAGB_IC). See Section 5.1.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Distances from the Galactic plane for various subclasses of carbon stars (see Section 6).
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Period–magnitude relations for Mira variables and candidates for Mira variables found from WISE data. See Sections 7.2 and 7.3.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Observed SEDs compared with simple dust shell models: eight IR CAGB stars (IR-CAGB_IC). See Section 5.1.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Comparison of distances obtained from observations (Gaia DR3 and Hipparcos) and the ones obtained from theoretical model SEDs (see Section 5.3).
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Spatial distributions of AGB stars (CAGB_IC and CAGB_NI) in Galactic coordinates.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Lomb–Scargle periodograms for six CAGB stars with known periods (AAVSO Miras). The top panels display OGLE4 (I-band) light curves for two selected CAGB stars. Subsequently, the following six panels present WISE light curves for all six CAGB stars. The corresponding AAVSO periods for these six CAGB stars are 413, 365, 1060, 445, 442, and 302 days. See Sections 7.2 and 7.3.
Paper: Infrared Properties of Carbon Stars in Our Galaxy
Authors: Kyung-Won Suh
Figure caption: Lomb–Scargle periodograms using WISE light curves for eight CAGB stars with unknown periods (AAVSO). They could be candidates for new Mira variables. Note that the secondary period was used for the last two objects. See Section 7.3.
Paper: Exploring the Maximum Magnitude versus Rate of Decline Relation for Novae in M31
Authors: J. Grace Clark, Kamil Hornoch, Allen W. Shafter, Hana Kučáková, Jan Vraštil, Peter Kušnirák, Marek Wolf
Figure caption: Top panel: The R-band M 15 distribution for our complete sample of M31 novae. The red region shows the M 15 values for the known recurrent novae, while the blue region shows the suspected recurrent nova systems. The long tail to fainter magnitudes results primarily from the extrapolation of the rate of decline of novae in the second quadrant of the MMRD relation. Bottom panel: The R-band M 15 distribution for our high-quality samples of M31 novae. The lightly shaded region shows the novae in our silver sample, while the dark green region shows novae with the best light curves in our gold sample.
Paper: Exploring the Maximum Magnitude versus Rate of Decline Relation for Novae in M31
Authors: J. Grace Clark, Kamil Hornoch, Allen W. Shafter, Hana Kučáková, Jan Vraštil, Peter Kušnirák, Marek Wolf
Figure caption: The R-band M  R  distribution for our sample of M31 novae. The dispersion of the distribution is characterized by a standard deviation σ = 0.89 mag, with an average given by 〈M  R 〉 = −7.57 ± 0.07. The mean of the distribution is in excellent agreement with the recent mean for Galactic novae found by Schaefer (2022).
Paper: Exploring the Maximum Magnitude versus Rate of Decline Relation for Novae in M31
Authors: J. Grace Clark, Kamil Hornoch, Allen W. Shafter, Hana Kučáková, Jan Vraštil, Peter Kušnirák, Marek Wolf
Figure caption: The MMRD relation for M31 based on the highest quality data from our Gold and Silver samples. Almost all of the novae in the Jitter class have been omitted as the large amplitude fluctuations made the determination of the fade rate particularly difficult. Restricting the sample to the novae with the most well-behaved light curves does not strengthen the MMRD relation. The fits shown (dashed and dotted lines) are reproduced from Figure 2.
Paper: Stellar Atmospheric Parameters of ∼11,000 RR Lyrae Stars from LAMOST Spectra
Authors: Jiangtao Wang, Jianrong Shi, Jianning Fu, Weikai Zong, Chunqian Li
Figure caption: The internal uncertainty of radial velocities for LRS and MRS as a function of S/N. The color represents the normalized number of parameters in the boxes. The panels (a)–(e) are the internal uncertainties of RV[l,metal], RV[l,Hδ], RV[l,Hγ], RV[l,Hβ], and RV[l,Hα] determined from S [l,metal], S [l,Hδ], S [l,Hγ], S [l,Hβ], and S [l,Hα], respectively. The panels (f) and (g) are the internal uncertainties of RV[m,metal] and RV[m,Hα] determined from S [m,b] and S [m,Hα], respectively. In each panel, the red line indicates the median within bins with an S/N of 5. The accompanying text in each panel specifies the σ for RV S/N values of 10, 20, and 50, respectively.
Paper: Stellar Atmospheric Parameters of ∼11,000 RR Lyrae Stars from LAMOST Spectra
Authors: Jiangtao Wang, Jianrong Shi, Jianning Fu, Weikai Zong, Chunqian Li
Figure caption: The single-exposure LRS and MRS of RRab EPIC 212182292. The top two panels illustrate the segments from the red and blue arms of the LRS, and the bottom two panels depict those from the MRS. The Balmer lines and Mg Ib triplets of LRS and MRS are highlighted with cyan lines.
Paper: Stellar Atmospheric Parameters of ∼11,000 RR Lyrae Stars from LAMOST Spectra
Authors: Jiangtao Wang, Jianrong Shi, Jianning Fu, Weikai Zong, Chunqian Li
Figure caption: The internal uncertainties of T eff, ﹩\mathrm{log}\,g﹩, and [M/H] are determined from LRS (left panels) and MRS (right panels) as a function of S/N. The color represents the normalized number of parameters in the boxes. The red curve represents the median of the best fit as a reciprocal function of the S/N, and its values at S/N = 10, 20, and 50 are given throughout the text.
Paper: Stellar Atmospheric Parameters of ∼11,000 RR Lyrae Stars from LAMOST Spectra
Authors: Jiangtao Wang, Jianrong Shi, Jianning Fu, Weikai Zong, Chunqian Li
Figure caption: The sky coverage of the RRL sample. The gray dots represent the RRL sample from five surveys located in the LAMOST field (decl. ≥ −10°). The blue dots and red crosses represent RRL sample with LAMOST LRS and MRS, respectively.
Paper: Stellar Atmospheric Parameters of ∼11,000 RR Lyrae Stars from LAMOST Spectra
Authors: Jiangtao Wang, Jianrong Shi, Jianning Fu, Weikai Zong, Chunqian Li
Figure caption: The G magnitude distribution with a bin width of 0.25 mag for our RRL sample (left) and their LAMOST spectra (right).
Paper: Advancing Solar Energetic Particle Event Prediction through Survival Analysis and Cloud Computing. I. Kaplan–Meier Estimation and Cox Proportional Hazards Modeling
Authors: India Jackson, Petrus Martens
Figure caption: Class distribution.
Paper: UPCluster-SZ: The Updated Catalog of Galaxy Clusters from the List of Planck Sunyaev–Zel’dovich Sources
Authors: Hyeonguk Bahk, Ho Seong Hwang
Figure caption: Comparison between redshift estimations of the confirmed clusters using our galaxy catalog detection method and the reference redshift, shown before (a) and after (b) applying the ﹩\bar{R}\leqslant 2﹩ cut. The symbol color and size represent different detection thresholds: blue, orange, and red correspond to thresholds of 7, 9, and 10, respectively. We define outliers as cases where the relative redshift difference ∣Δz∣/(1 + z) exceeds 0.015, which corresponds to a velocity limit of 4500 km s−1. The dotted lines in the figure represent this velocity limit. The legend provides the total outlier fraction for each threshold, enclosed in parentheses. The bottom and right panels show the outlier fraction as a function of redshift, sharing the color scheme with the main panels.
Paper: UPCluster-SZ: The Updated Catalog of Galaxy Clusters from the List of Planck Sunyaev–Zel’dovich Sources
Authors: Hyeonguk Bahk, Ho Seong Hwang
Figure caption: Top: cluster detection of PSZ2 G031.37–71.95 using the catalog of galaxies with spectroscopic redshifts. The galaxies that comprise the detection peak are shown by blue circles, while all the available spectroscopic redshift galaxies inside a radius of ﹩15^{\prime} ﹩ from the SZ center are represented by black circles. The searching radius is shown by the thick black circle, where its center is located at the PSZ2 centroid, marked as a black plus sign. The contour of the MILCA Compton y-map provided by Planck is overlaid on the DESI Legacy Survey DR10 image with thin solid (positive) and dashed (negative) lines. Bottom: the number count of spectroscopic redshift galaxies at Δv < 4500 km s−1 with respect to the trailing redshift. The bin size is smaller than the velocity range by factor of 11, hence its name “boxcar count.” Our detection threshold of nine galaxies is shown by the dotted line. The corresponding detection peak for the blue-circled galaxies in the velocity range is annotated by the blue arrow with its corresponding redshift (z = 0.137).
Paper: UPCluster-SZ: The Updated Catalog of Galaxy Clusters from the List of Planck Sunyaev–Zel’dovich Sources
Authors: Hyeonguk Bahk, Ho Seong Hwang
Figure caption: The normalized histogram of the detected cluster signal using our method for confirmed clusters vs. ﹩\bar{R}﹩, which represents the mean distance of member galaxies from the PSZ2 center. The dotted gray line denotes all cluster detection signal without any selection process, and the red line shows the selected peak by the number of galaxies and the galaxy center offsets relative to the PSZ2 center. The green line shows the detections of each confirmed cluster, whose redshifts are the closest to their reference redshifts. The detections of candidate clusters show an additional bump on ﹩\bar{R}\gt 2﹩, which is not significant for the confirmed clusters.
Paper: UPCluster-SZ: The Updated Catalog of Galaxy Clusters from the List of Planck Sunyaev–Zel’dovich Sources
Authors: Hyeonguk Bahk, Ho Seong Hwang
Figure caption: The schematic flowchart of our compilation process. PSZ2 objects can be divided into 1203 confirmed clusters and 450 candidates. Among the confirmed clusters, 1094 clusters have their redshift information, and 109 clusters do not have the redshift before the inclusion of the cluster catalogs (see Sections 3.1 and 2.2) and validation using the galaxy catalogs (see Sections 2.3 and 3.3). Cluster catalogs in the list are abbreviated with Name-ReferenceYear, which can be identified with the ordinal numbers that correspond to column (1) in Table 1.
Paper: UPCluster-SZ: The Updated Catalog of Galaxy Clusters from the List of Planck Sunyaev–Zel’dovich Sources
Authors: Hyeonguk Bahk, Ho Seong Hwang
Figure caption: The sky distribution of the PSZ2 clusters and candidates. (a) Confirmed galaxy clusters (gray; 1203) and the candidate clusters (red; 450) in PSZ2. (b) Galaxy clusters whose spectroscopic redshifts are available (blue; 1094) and clusters (or candidates) whose spectroscopic redshifts are not available (red; 559) in PSZ2. The solid line shows the galactic plane, and the dashed lines correspond to the galactic latitude b = ±10°. The blue shaded region shows the SDSS footprint.
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: The four components of the ERM are distinguished by the different background colors. In this paper, the data preprocessing includes the normalization of spectral data. The different colored blocks represent the various features extracted from the samples for feature extraction, and the model training provides an example of selecting the number of groups as four. In the model training, the different colored blocks in feature grouping and feature crossover represent various features of the samples. The multiplication sign indicates the multiplication of the features at the corresponding position, which is used to obtain the crossover features. The different colored blocks in the regression ensemble represent the regression equations in which the features of the corresponding colored blocks are used as the dependent variables. The colored blocks within positive and negative error intervals depict the error ranges of the regression equations. The top half of the model, with a light yellow background, represents the error intervals for positive examples, while the bottom half, with a light gray background, signifies the error intervals for negative examples. Various data flows are illustrated using distinct colors. The brown arrows denote the flow of data from the samples to be classified, the black arrows signify the data flow during the model training phase, and the thin black lines indicate the flow of the training data.
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: The top panel shows the normalization of the spec-56094-kepler05B56094_sp08-044.fits.gz sample. The upper half of the figure shows the raw spectrum in the wavelength range 3800–5600 Å. In the figure, the black line is the original spectrum, the red line is the spectrum after removing the radial velocity, which is so small that the two almost overlap, and the green line is the fitted pseudocontinuum spectrum. The bottom half of the figure shows the results of the completed processing of the sample, where the vast majority of the spectral fluxes have been normalized to between 0 and 1, while the main features of the spectra are well preserved.
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: Changes in precision for Am_ERM on the Am noisy test set with different S/Ng as the divergence score threshold changes.
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: Changes in precision for Ap_ERM on the Ap noisy test set with different S/Ng as the divergence score threshold changes.
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: Subclass distribution of the Am and Ap catalogs in LAMOST provided by Shang et al. (2022).
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: Changes in accuracy, precision, and recall for Am_ERM on the Am training set as the divergence score threshold changes.
Paper: A Sample of Am and Ap Candidates from LAMOST DR10 (v1.0) Based on the Ensemble Regression Model
Authors: Hai-Feng Yang, 海峰 杨, Rui Wang, 瑞 王, Jiang-Hui Cai, 江辉 蔡, A-Li Luo, 阿理 罗, Bing Du, 冰 杜, Yan-Ting He, 艳婷 贺, Mei-Hong Su, 美红 苏, Chen-Hui Shi, 晨辉 史, Xu-Jun Zhao, 旭俊 赵, Ya-Ling Xun, 亚玲 荀, Yi-Nan Yuan, 艺楠 员
Figure caption: Changes in accuracy, precision, and recall for Ap_ERM on the Ap training set as the divergence score threshold changes.