dataesr/scientific-paragraphs-categorization huggingface dataset:
A second advantage is easily satisfied data requirements. Data that will allow application to a wider range of taxa and spatial scales are becoming increasingly available. Initiatives like BIEN are being developed for plant distributions and assemblage composition in China  (Fang et al. 2012)  and Europe  (Dengler et al. 2011). Similar initiatives also exist for mammals  (Thibault et al. 2011)  and birds (e. g. , Breeding Bird Survey; available online). 17 Moreover, paleo-assemblage and paleo-occurrence data are also becoming more available through recent database efforts (e. g. , Neotoma; available online). 18 Paired with the growing availability of high-quality, spatially resolved paleoclimate estimates from general circulation models (e. g. ,  Liu et al. 2009 ) and climate niche reconstructions based on phylogeny  (Evans et al.
ACKNOWLEDGMENTS We thank  Robert Colwell  for his thoughtful comments. This work was conducted as part of the  Botanical Information Ecology Network (BIEN) working group , supported by the  National Center for Ecological Analysis and Synthesis (NSF  grant # EF-0553768 ), the  University of California Santa Barbara , and the state of California. The BIEN working group was also supported by iPlant (NSF grant # DBI-0735191 ). We thank many collaborators for sharing data with BIEN. A full list of data providers is available at http://bien. nceas. ucsb. edu/bien/people/data-contributors/. B. Blonder was supported by a  NSF  predoctoral fellowship and a  Nordic Research Opportunity  award cosponsored through the  Danish National Research Foundation's Center for Macroecology, Evolution and Climate.
Section 2. 2), having Triple Graph Grammars (Tggs) as a formal background. The language makes use of patterns to describe allowed and forbidden relations between two models. Patterns are compiled into Tgg rules to perform forward and backward transformations that can later be executed with classical Gbt engines (e. g. , Fujaba  [83] ). In  [37] , de Lara and Guerra proved that this compilation scheme is sound, terminating and confluent; the result has been later extended in  [46]  to handle attribute conditions. Termination criteria for Mpls directly benefit from the vast and active literature on imperative and object-oriented programming languages. These criteria usually rely on abstract interpretations built on top of low-level programming artefacts (like pointers, variables and call stacks).
Similarly, Blech, Glesner and Leitner  [16]  proved the bisimulation between StateChart models and Java-like generated code. Rahim and Whittle proved in  [93]  a simplified form of what they called semantic conformance, i. e. the fact that a code generator (from Uml State Machines to Java) preserves the semantics of the original metamodel. Semantic considerations are injected as annotations into the generated Java code that is later automatically model-checked by Java PathFinder  [117]. This approach has two major drawbacks: one has to inspect the generated code to insert the annotations, and the semantic conformance only covers the properties specified by these annotations. Another way of capturing the semantic preservation consists of expressing the correctness through an external language over the input and the output models.
In  [114]  Varró and Pataricza use Ctl (Computation Tree Logic)  [30]  as a language to state properties on each side of the transformation. They then prove that the Ctl formulaestill hold when transforming StateCharts into Petri Nets. Both metamodels have a close state-based semantics, but in the general case, it seems more difficult to state how formulaeat each side are considered equivalent, especially if the languages at each side are different. Behaviour Refinement Instead of proving preservation, one may be interested in refinement, meaning that every behaviour of the input model is allowed by the output (although the output may present more behaviours). Heckel and Thöne  [96]  propose a notion of behaviour refinement of Gbt models. These models are in fact model transformations specified over source and target metamodels that allow expressing system configurations.
Type I: Transformation-Independent and Input-Independent Properties that hold independently of the transformations expressed in a particular Tl are normally proved once and for all. Performing tool-assisted proofs is cumbersome: it requires to reflect the semantics of the underlying Tl directly in the Fv tool, which is a heavy task. For example, formally proving termination for Gbt with a theorem-prover requires to express the semantics of pattern-matching in the theorem-prover's language. Therefore, these kinds of proofs are usually presented mathematically. Barroca et al. [9]  prove termination and confluence of DslTrans inductively, following the layered syntactic construction of the language's transformations. Ehrig et al. [41]  address termination of Gbts inductively, by proving termination of deleting and non-deleting layers separetely.
At least two different logics are becoming popular: the Calculus of Inductive Constructions, inspired from typed lambda calculi, at the basis of Coq  [13] , and the Constructive Type Theory at the foundation of NuPrl  [33]. These formalisms have been used in the context of Mde to extract certified transformations: Calegari et al. [25]  used Coq for handling Atl transformations, whereas Poernomo  [91, 92]  used directly NuPrl to formalise Mof. Unfortunately, both contributions are only demonstrated on the famous Class Diagram to Relational Databases classical example. The effort of such a formal specification in logics that are not directly intuitive for Mde engineers seems to hinder its wide applicability.
The generated state space is then used to prove if properties hold for all input models of the transformation. Varró and Pataricza  [114]  used model checking to prove that dynamic consistency properties were preserved in a model transformation from statecharts to Petri Nets. Rahim and Whittle  [93]  used the Java PathFinder model-checker  [117]  to check the semantic conformance of the Java code produced by two industrial code generators (Rhapsody and Visual Paradigm) with respect to the semantics of Uml State Machines: they annotated the output Java program with property specifications that the model-checker can then handle automatically. Theorem Proving Asztalos et al. [73]  proposed deduction rules that can be applied to model transformation rules (formalized as graph rewriting) to prove or disprove a property.
The deduction rules were implemented as a verification framework in Vmts (Visual Modeling and Transformation System) and was used to verify a refactoring transformation on business process models. Paige et al. [87]  compared two approaches for the verification of model conformance checking and multi-view consistency checking (Mvcc): with Pvs, a popular theorem prover based on set theory; and with Eiffel, an object-oriented language. Nevertheless, performing Mvcc checking requires actually executing the generated Eiffel code. Giese et al. [55]  proposed formalizing Modelto-Code transformations using Tggs in Fujaba, further verified within Isabelle/Hol. Again with Isabelle/Hol, Blech, Glesner and Leitner  [16]  proved that a code-generation transformation preserves the bisimulation between StateChart models and Java-like code.
Isabelle/Hol was also used by Schätz  [102]  to prove the conformance of output models. Marković and Baar  [7, 74]  proved that a Java implementation of some of their refactoring rules for Uml class diagrams containing Ocl constraints preserve the instantiation semantic of class diagrams (although the reimplementation in Java of the refactoring rules can be seen as a non-direct proof of the rules' Ocl implementation). Lano and Kolahdouz-Rahimi  [67]  used the B Method to prove several properties over Uml-Rsds (syntactic correctness, uniqueness, and transformation confluence), from which trustable Java code is generated automatically. B was also used by Ledang and Dubois  [68]  to prove that user-defined invariants hold over Gbts. Barbosa et al. [8]  used the Maude's Interactive Theorem Prover to prove a relatively simple form of semantic preservation.
Eiffel itself  [14]  or the GnatProve Project for Ada  [112] ). However, this still need more investigations in order to apply to current metaprogrammed transformation languages. Cariou and his colleagues  [27, 28]  studied the use of Ocl for the specification of contracts for model transformations: they associate preconditions over the input model for being eligible to transformation, postconditions on the output model for being considered as a valid result, and other constraints expressed over the pair of input/output models that track how model elements evolve during transformations. They also applied their technique for the specification of Dsl semantics (following the  operational approach, cf. Section 2. 4) and have demonstrated the feasibility of the approach on Uml state machine executions  [27].
Based on Ocl, the authors noticed limitations due to the mono-context nature of Ocl and the difficulty of applying such approach on exogeneous transformations because it requires the manipulation of an amalgamated metamodel (i. e. a metamodel that includes both the source and the target). Guerra, de Lara, Wimmer et al. [47]  proposed PaMoMo, a platform for declaratively specifying requirements independently of the language used to perform the transformation. The visual contracts specifying the requirements can express pre-/post-conditions (i. e. conditions for a model to be eligible for transformations, and patterns in an output models to capture required or forbidden configurations for the result) and invariants for the input/output pair of models, and can be automatically translated into Qvt-R for checking that a given transformation (expressed using Gbt) respects them.
Acknowledgments The authors warmly thank the anonymous reviewers who suggested many improvements that helped clarifying the paper, and several contributions that were missing. This work is partially supported by the  Luxemburgish Fonds National de la Recherche (Fnr) , the  Natural Sciences and Engineering Research Council of Canada (Nserc) , the  Ibm Canada Center for Advanced Studies (Cas) , the  Automotive Partnership Canada (Apc)  in the  Necsis  project, and by the  French Agence Nationale pour la Recherche (Anr)   Ins Project GEMOC  ( ANR-12-INSE-0011 ).
5-2. 0% of a resolution element. For spectral line flux, the repeatability is better than 6%, which improves to 1-2% for spectra corrected for pointing offsets. The continuum repeatability is 4. 4% for the SLW band and 13. 6% for the SSW band, which reduces to ∼1% once the data have been corrected for pointing offsets. Observations of dark sky were used to assess the sensitivity and the systematic offset in the continuum, both of which were found to be consistent across the FTS detector arrays. The average point-source calibrated sensitivity for the centre detectors is 0. 20 and 0. 21 Jy [1 σ; 1 hour], for SLW and SSW. The average continuum offset is 0. 40 Jy for the SLW band and 0. 28 Jy for the SSW band.
The designations of the two central detectors for the SSW and SLW arrays are SSWD4 and SLWC3 respectively. In Section 2 the FTS calibration sources are introduced. Section 3 details the data reduction procedures that were applied beyond the standard pipeline. Section 4 investigates spectral line fitting of FTS data and the repeatability of observations of line sources. The continuum spectra of the line sources are considered in Section 5. Comparisons to planet and asteroid models are made in Section 6, and with SPIRE photometer observations in Section 7. The importance of an extensive set of FTS observations of the SPIRE dark sky field is discussed in Section 8, which are used to assess the FTS sensitivity and uncertainty on the continuum for all detectors. The findings are summarised in Section 9.
AFGL4106 AFGL4106 is fainter and has fewer previous observations than the other three sources, but was added to the programme to fill a gap in coverage, and ensure at least one calibration source was available on every SPIRE FTS observing day. It is an evolved massive star surrounded by a dust shell in the post-red supergiant phase, and known to be part of a binary system  (Molster et al. 1999). It has ongoing mass-loss, and is surrounded by a bow shaped emission complex that extends to 5-10 from the star  (Van Loon et al. 1999 ). In the mid-infrared, the dust distribution is clumpy with a size of 3. 4 × 3. 3  (Lagadec et al. 2011). Infrared Astronomical Satellite (IRAS;  Neugebauer et al. 1984 ) 100 µm observations (Miville-Deschênes & Lagache 2005) show this source to be embedded in a region of Galactic cirrus, which is evident in the SPIRE photometer data (see Fig.
DATA PROCESSING All FTS data presented were reduced with the standard Herschel Interactive Processing Environment (HIPE; Ott 2010) pipeline  (Fulton et al. in preparation) , or standard pipeline tasks where required, with HIPE version 13 and spire cal 13 1 calibration tree used for the main results presented. There can be a number of considerations for FTS data on top of a standard reduction, and some of these are explored in this section.
Line measurements The two main quantities that were obtained from fitting spectral lines are the integrated line flux (I) and the line centre position. For point-source-calibrated FTS data, I can be calculated in W m -2 from the fitted sinc function parameters by integrating Equation 1 over frequency as I = f (ν : p) dν = 10 -26 p010 9 π p2. (3) The signal-to-noise ratio (SNR) was also estimated per line, using the fitted amplitude and the local standard deviation of the residual, obtained after subtracting the combined fit. The sinc fit also provides the line centre position, which can be expressed as a radial velocity in the LSR frame, relative to the measured laboratory rest frame line position in km s -1. Line identifications were checked against  Wesson et al. (2010) , with the rest frame line positions taken from the Cologne Database for Molecular Spectroscopy  (Müller et al.
This difference indicates that pointing stability is a more significant source of uncertainty on the continuum than intrinsic variability for these sources, which appears negligible. There is a high scatter for AFGL4106 in SLW, due to the extended background. The spread of continua, as a percentage of the mean level is shown to the bottom right of Fig. 7 , and ranges from 5% to 15% for data not corrected for pointing offset, with mean values for the four main line sources of 4. 4% for SLW and 13. 6% for SSW. After correcting for pointing offset, these values fall to less than 2%, however the relative method used to correct the data does inherently correct for intrinsic variability, by assuming the single reference observation for a particular source should match all other observations for that source, regardless of any brightness variation.
The ranges used were 600-900 GHz for SLW and 1100-1500 GHz for SSW. To provide a single value per observation, the median ratio was taken across the frequency range, and the standard error on the mean taken as a 1 σ uncertainty. Fig. 27  shows the resulting ratios with and without correcting the data for pointing offset. Before correcting for pointing offset, the average HR ratio for Uranus shows an offset from 1. 0 of 1% and 3% for SLW and SSW, with uncertainties of 2% and 5%, respectively (see Table  5 ). After correcting for pointing offset, the SLW ratios are approximately unchanged, as expected, whereas HR SSW ratios improve to a mean ratio of 1. 0, with <1% spread. These results are consistent with the spectral line flux repeatability presented in Section 4. 2. For Neptune the offset from a ratio of 1.
0 is 2% regardless of correcting the data for pointing offset, however the associated spread for SSW improves from 2% to 1% after correction. Before pointing offset is corrected, the average LR Uranus ratio is 0. 99±0. 02 for SLW and 0. 96±0. 05 for SSW. After correction, the uncertainty of these ratios improve to 1% for SSW, with a mean ratio of 1. 0. For Neptune the average LR ratios are 1. 02±0. 01 for SLW and 1. 00±0. 02 for SSW. After correcting the LR data for pointing offset, the ratios show a more consistent 2% shift from 1. 0, with the associated SSW scatter reduced to 0. 01. The systematic shift in the ratios of 2%, when comparing to the Neptune model, is consistent with the findings of  Swinyard et al. (2014). There is more consistency between the "before" and "after" observations and between the two bands for both sets of ratios, compared to those presented in  Swinyard et al.
'corr' indicates the ratios for data corrected for pointing offset. Ceres, Pallas and Vesta have ratios consistently nearest to 1. 0 due to their more recent models of  Müller et al. (2013). The average ratios for these three asteroids after correcting for pointing offset are 1. 06±0. 07 for SLW and 1. 09±0. 02 for SSW. Note that due to a higher scatter in the ratio values, the y-scaling is wider for these plots than the planet equivalent ratio plots in Fig. 27. Dec were used as the coordinate input. The average photometry was taken for each source, and for each band, and the associated uncertainties added in quadrature. Photometer observations of line sources and stars that are used in this paper are summarised in Table  D1. To generate synthetic FTS photometry over a SPIRE photometer waveband, a point-source-calibrated spectrum was weighted by the relevant photometer RSRF, including the aperture efficiency, and the result integrated.
Figure28. Data to model ratios for several asteroids. HR ratios are shown with filled symbols and LR ratios with the corresponding open symbols. The LR symbol for Juno is the same cross filled square, but larger in size (and at an earlier OD to the HR observations). 'corr' indicates the ratios for data corrected for pointing offset. Ceres, Pallas and Vesta have ratios consistently nearest to 1. 0 due to their more recent models of Müller et al. (2013). The average ratios for these three asteroids after correcting for pointing offset are 1. 06±0. 07 for SLW and 1. 09±0. 02 for SSW. Note that due to a higher scatter in the ratio values, the y-scaling is wider for these plots than the planet equivalent ratio plots in Fig. 27.
ACKNOWLEDGMENTS We thank the referee,  J. P. Maillard , for his constructive comments, which helped improve the paper. SPIRE has been developed by a consortium of institutes led by  Cardiff Univ. (UK)  and including:  Univ. Lethbridge (Canada) ;  NAOC (China) ;  CEA ,  LAM (France) ;  IFSI ,  Univ. Padua (Italy) ;  IAC (Spain) ;  Stockholm Observatory (Sweden) ;  Imperial College London ,  RAL ,  UCL-MSSL ,  UKATC ,  Univ. Sussex (UK) ; and  Caltech ,  JPL ,  NHSC ,  Univ. Colorado (USA). This development has been supported by national funding agencies:  CSA (Canada) ;  NAOC (China) ;  CEA ,  CNES ,  CNRS (France) ;  ASI (Italy) ;  MCINN (Spain) ;  SNSB (Sweden) ;  STFC ,  UKSA (UK) ; and  NASA (USA). This research is supported in part by the  Canadian Space Agency (CSA)  and the  Natural Sciences and Engineering Research Council of Canada (NSERC).
2015). BOSS collected spectroscopic data from 2009 December to 2014 July. • The Apache Point Observatory Galaxy Evolution Experiment (APOGEE; S. Majewski et al. 2015 , in preparation) used a separate 300-fiber high-resolution (R ∼ 22, 500) H-band spectrograph to investigate the composition and dynamics of stars in the Galaxy. The target stars were selected from the database of the Two Micron All-Sky Survey (2MASS;  Skrutskie et al. 2006) ; the resulting spectra give highly accurate stellar surface temperatures, gravities, and detailed abundance measurements. APOGEE gathered data from 2011 May to 2014 July. • The Multi-Object APO Radial Velocity Exoplanet Large-area Survey (MARVELS; J. Ge et al. 2015 , in preparation) used a 60-fiber interferometric spectrograph to measure high-precision radial velocities of stars to search for extra-solar planets and brown dwarfs orbiting them.
MAR-VELS gathered data from 2008 October to 2012 July. The SDSS data have been made available to the scientific community and the public in a roughly annual cumulative series of data releases. These data have been distributed  (Thakar 2008b)  in the form of direct access to raw and processed imaging and spectral files and also through a relational database (the "Catalog Archive Server", or "CAS"), presenting the derived catalog information. As of DR12 these catalogs present information on a total of ∼470 million objects in the imaging survey, and 5. 3 million spectra. The Early Data Release (EDR;  Stoughton et al. 2002) , and Data Releases 1-5 (DR1;  Abazajian et al. 2003, DR2; Abazajian et al. 2004, DR3; Abazajian et al. 2005, DR4; Adelman-McCarthy et al. 2006, and DR5; Adelman-McCarthy et al.
DR12 includes almost 2. 5 million BOSS spectra of quasars, galaxies, and stars over 9,376 square degrees: 155,000 SEGUE-2 spectra of 138,000 stars (as released in DR8), and 618,000 APOGEE spectra of 156,000 stars. It also includes the first release of MARVELS data, presenting 197,000 spectra of 5,500 stars (3,300 stars with > 16 observations each). Because some BOSS, APOGEE, and MARVELS scientific papers have been based on the DR11 sample, this paper describes the distinction between DR11 and DR12 and the processing software for the two data sets, and how to understand this distinction in the database. The data release itself may be accessed from the SDSS-III website 140  or the DR12 page of the new pan-SDSS website. 141 DR11 is similarly available through the same interfaces. The outline of this paper is as follows.
The MARVELS instrument  (Ge et al. 2009 ), the W. M. Keck Exoplanet Tracker, uses an innovative dispersed fixed-delay interferometer (DFDI) to measure stellar radial velocities, by observing the movements of stellar lines across the fringe pattern created by the interferometer. The wavelength coverage of the interferometer is 5000 Å < λ < 5700 Å and it simultaneously observes 60 science fibers. MARVELS radial velocities (RVs) are differential measurements, based on the shift of a star's fringing spectrum at the current epoch relative to one from the template epoch. For more details on the MARVELS program and DFDI instruments see  Eisenstein et al. (2011); Erskine & Ge (2000) ;  Ge (2002) ;  Ge et al. (2002 Ge et al. ( , 2009)) ;  van Eyken et al. (2010)  and J. Ge et al. (2015, in preparation).
See also Table  2  of  Ahn et al. (2012)  for additional changes to the hardware. Note. -There are two BOSS spectrographs, each with a red and blue camera. Thus R2 refers to the red camera on the second spectrograph, which accepts light from fibers 501-1000. The August dates in the table above refer to the summer shutdowns. As in previous BOSS data releases, a unique tag of the idlspec2d spectroscopic pipeline software is associated with each unique sample of publicly released data. 142 Three tagged reductions of three separate samples are being released at the time of DR12. One (v5 6 5) is the "DR11" version that defines a homogeneous sample of BOSS data taken through Summer 2013; this is the version used in the cosmological analyses described in Section 4. 2 above. A second label (v5 7 0) defines the main DR12 BOSS cosmological survey at its point of completion.
A third tag (v5 7 2) is associated with the several extra observing programs undertaken with the BOSS spectrographs in Spring 2014 following the completion of the main BOSS survey program (Section 4. 1, Appendix A). These data-release software versions are summarized in Table  4. Many of the pipeline changes for the ancillary programs involved bookkeeping and special cases for plates drilled with either fewer or more flux calibration stars. In addition the SEQUELS plates targeted ELGs at high redshift, so the upper redshift limit of the galaxy template fitting  (Bolton et al. 2012 ) was extended from z = 1 to z = 2. Thus DR12 includes several thousand SDSS galaxy spectra with tabulated redshifts above z = 1.