dataesr/scientific-paragraphs-categorization huggingface dataset:
We obtained the mean resultant vector R from the unit vectors corresponding to all the taps in a sequence. We used two measures of phase synchronization: consistency and accuracy. Consistency corresponds to the length of vector R, ranging from 0 to 1, where 0 refers to a uniform distribution of angles around the circle (i. e. , lack of synchronization), and 1 to maximum consistency (no variability). Accuracy corresponds to the angle of vector R (θ or relative phase, in degrees), and it indicates whether participants tapped before (negative angle) or after (positive angle) the pacing event. Accuracy was calculated only if participants' synchronization performance was above chance (null hypothesis = random distribution of data points around the circle), as assessed with the Rayleigh test for circular uniformity  (Fisher, 1995; Wilkie, 1983).
Statistical analyses Statistical analyses were performed in R (version 4. 2. 2;  R Core Team, 2022). The measure score distribution shapes were described in terms of skewness and excess kurtosis (i. e. , kurtosis -3) using the moments package in R. In order to reduce reliance on normal distributions in the task scores, robust rank-based versions of t-tests, ANOVAs and regressions were used where possible, using the Rfit package in R  (Kloke & McKean, 2012). Each BAASTA variable was first tested for an effect of gender, and then separately for the effects of age (in years) and age group (categorically) using the rfit function. Probability values were calculated from the resulting t statistic for effects of gender and age, and as an omnibus test via the "drop in dispersion test" for the effect of age group  (Kloke & McKean, 2012).
Test-retest reliability We compared the first and the second testing sessions by Wilcoxon-Mann-Whitney test (wilcox. test R function, "paired"). Rejection of the null hypothesis implies a significant difference between the two sessions and reveals a systematic error that may result from an experimental bias such as the effect of weariness or learning. Correlation of scores between the two sessions was calculated by Spearman rank correlation (using cor. test R function). To control for sources of error due to chance (random error; e. g. , biological variability), we calculated the intraclass correlation coefficient (ICC3,1) using the icc function from the irr R package  (Gamer et al. , 2019). The ICC3,1 is considered a good index of test-retest reliability with the same experimenter because it does not include the variance associated with systematic error (bias)  (Brozek & Alexander, 1947; Fleiss, 1986; Weir, 2005).
In sum, diagnostic scores indicate that the data entering in the calculation of the norms were of high quality. We ran preliminary analyses on the final dataset to test whether there were effects of gender on any task measures, finding only a greater hit rate for males on the BAT medium tempo trials (t(106) = 2. 14, p =. 035). As no further gender effects were found on the main BAT d' measures (p >. 15), nor across any other measures (p >. 09), data were not separated by gender for subsequent analyses.
Norm tables We analyzed data collected at the Test phase to generate norm tables. The measures of timing and rhythmic abilities reported in the tables are summarized in Table  1 , with reference to the tables in which the norms are presented. The table also includes additional measures which are not reported in the norm tables, but that can be found in more detailed tables in Supplementary Materials. The norm tables report skewness and excess kurtosis for the distributions, the mean and SD, as well as percentile scores (0, 25 th , 50 th , 75 th , and 100 th percentile) for the overall group of participants, and separately for the four age groups (18 to 21, 22 to 29, 30 to 54, and 55 to 87 years). Significant differences between the four age groups are indicated in the tables, as well as between tempos or other comparisons within the same task (unpaced initial vs.
, 2022) , and does not require prior calibration. A previous comparison study showed that this tablet version of BAASTA can successfully replicate the results obtained with paced tapping on a lab computer  (Zagala et al. , 2021). Despite these advantages, however, one of the shortcomings of relying on auditory recordings is the sensitivity of the measurement to ambient noise. Even though BAASTA tests should be ideally administered in a sound-proof room, this condition may be harder to meet when the tests are performed outside of the lab (in a school class, hospital), or in more ecological settings. Thus, we developed methods affording data quality checks for ensuring the reliability of the collected data when BAASTAtablet is used in less-than-ideal testing settings. To this aim, we proposed two metrics (match score and match IQR) which can attest whether data quality is excellent, identify any trials needing reviewing, and provide a basis to select the best quality trials in situations where we know that the quality of audio recordings may be affected (e.
g. , testing in ecological settings). These quality checks, provided on a trial-by-trial basis, are critical for BAASTA users to make informed decisions about the data before they are included in further analyses or used for diagnosis purposes in clinical studies. To our knowledge, this is the first battery of timing and sensorimotor tests to be validated on a mobile device in the adult population across the lifespan. Norms play an important role in defining cut-off scores for impaired performance in various clinical groups, and for ensuring comparability across the lifespan and studies. The norms are provided for four age groups of comparable sample size. Even though we observed between-group age differences only in a few cases, we found relations between most BAASTA tasks and age (as a continuous dimension).
These findings suggest that age should be considered to compare data collected in future studies with the battery, by choosing the appropriate age group and/or testing condition or stimulus material. Test-retest reliability measures reveal differences among BAASTA tasks, spanning from good to excellent reliability. For example, among perceptual tests, the BAT  (Iversen & Patel, 2008) , and among sensorimotor tests, paced tapping to music (e. g. ,  Repp, 2005; Repp & Su, 2013) , both display excellent test-retest reliability (with ICC ~ 0. 76). Only one measure across tasks revealed quite low test-retest reliability, namely motor variability (CV of ITI; e. g. , ICC < 0. 35 in unpaced tapping tests, or in individual conditions in paced tapping with music or synchronization-continuation). This suggests that measures such as accuracy/consistency in paced tapping are preferable over other measures (e.
In sum, the adaptation of BAASTA for use on a mobile device, the availability of norms for the adult population, and the possibility of using BTI as a valuable composite score is expected to increase the use of the battery in adult healthy individuals to quantify individual differences (e. g. , Dalla  Bella et al. , 2023; Fiveash et al. , 2022) , and in clinical populations with poor timing and rhythmic abilities (e. g. , Parkinson,  Benoit et al. , 2014; Grahn & Brett, 2009; ADHD, Puyjarinet et al. , 2017; speech and language impairement, Bégel et al. , 2022; Corriveau & Goswami, 2009; Falk et al. , 2015; Ladányi et al. , 2020; Lense et al. , 2021; Autism Spectrum Disorder, Allman et al. , 2011). A mobile solution for assessing timing and rhythmic abilities, particularly appealing due to its portability and accessibility to the public, facilitates remote testing of participants with disabilities who cannot reach the laboratory, while ensuring high data reliability (with the caveats linked with the use of audio signal).
Acknowledgements and funding information The research was funded by a maturation grant from  French SATT AxLR  ( YOURHYTHM  project), and by funding from a  Discovery Grant  ( RGPIN-2019-05453 ) from the  Natural Sciences and Engineering Research Council of Canada (NSERC) , and by the  Canada Research Chair program  (CRC in music auditory- motor skill learning and new technologies ) to SDB. We wish to thank  Camille Gaillard ,  Paulina Herrera ,  Gabrielle Tessier ,  Anais Bédard ,  Justine Daoust  and  Mathilde Rochette  for their help in participant recruitment and data collection.
Medication assessment Medication data were retrieved from the medical records of participants. It included mainly antipsychotics, mood stabilizers, benzodiazepines, anticholinergics, and antidepressants. Mood stabilizers comprised lithium carbonate and antiepileptic medications (valproic acid, carbamazepine, pregabalin, topiramate, and phenytoin). The benzodiazepines included lorazepam, clonazepam, alprazolam, diazepam, alprazolam, and bromazepam. Anticholinergics consisted of trihexyphenidyl. Antidepressants were divided into two groups, i. e. , tricyclic antidepressants (TCA, including amitriptyline, clomipramine, and imipramine) and other antidepressants (venlafaxine, sertraline). The total anticholinergic burden was calculated based on the updated version of the Anticholinergic Drug Scale (ADS), where each medication was assigned a numerical value from 0 to 3, depending on their anticholinergic strength, and the overall ADS score for a patient was calculated by summing the values of all scheduled medications used by each participant  [28].
Statistical analysis Data were analyzed using SPSS software version 25. Categorical data were reported as absolute frequencies and percentages, whereas quantitative variables were expressed as means and standard deviations. The BACS composite score (z-score) was calculated by standardizing the total score over that of the healthy control group. This calculation was based on a healthy control group from a previously validated study using the same sample of patients with schizophrenia  [37]. The independent-sample t-test was used to compare the composite score of the BACS total score and subtests with the medication groups. The Pearson correlation test was used to evaluate the association between continuous variables. To assess the association between each subtest of the BACS scale with the ADS scale, the latter was grouped into five categories based on their ADS scores: no anticholinergic burden (ADS score = 0), low anticholinergic burden (ADS score = 1 or 2), moderate anticholinergic burden (ADS score = 3 or 4), high anticholinergic burden (ADS score = 5 or 6), or very high anticholinergic burden (ADS score = above 6).
1993; Fischer, 2003). The experiments were done on the web using Gorilla Experiment Builder (www. gorilla. sc; Anwyl-Irvine et al. 2020), and participants gave electronic  [12]  Participants were presented with audio files previously recorded by native speakers of each language. This decision was motivated by the fact that Greek NCIs are emphatic, while their homophonous PSIs are not. Therefore, we needed the oral stimulus for the Greek version of the experiment. To ensure consistency across languages, we decided to present all items in the three experiments auditorily.
Details of the planned statistical analysis For the AJT, data from sliding bar were converted into a numerical data point ranging from 1 to 100 (1 = unacceptable and 100 = acceptable). Responses from each participant were checked to establish whether they could rate the acceptability of the first four practice items correctly; if they did not, they were then excluded from the analysis. No participants had to be excluded. For the PST task, results were coded for target readings in a binary fashion (0 = existential reading and 1 = single negation reading). We ran all analyses in the R environment (R Core Team 2020; Bates et al. 2015 for the lme4 package), and we used separate models for each task and each language dataset, leading to six final models, details of which we report below. Considering that the data elicited in each task was different, we employed distinct modelling.
For the AJT, we used linear mixed effect models with random effects for participant and item  (Baayen, Davidson & Bates. 2008). We fitted the models for this task to the centered response data given by the participants in the sliding bar. For the PST, we used generalized mixed-effects logistic regressions models and we fitted them to the binomial response data, coded as 0 for the existential reading and 1 for the single negation reading. We first ran the omnibus test and explored planned pairwise comparisons with the lsmeans package  (Lenth, 2016)  to see if participants treated the three critical conditions differently from the six control ones. We report all intercepts from the omnibus models in each table.
experimental materials on Romanian, Russian, and Greek, respectively. We also extend this gratitude to all those who volunteered to distribute the experiment and participated in it. We thank the three reviewers of Journal of Linguistics for their detailed and helpful comments. We acknowledge financial support from  Spanish Ministerio de Ciencia e Innovación  (grants  POID2020-112801GB-100  and  PGC2018-096380-B-100 ),  Generalitat de Catalunya  (grant  2021SGR00787 ),  ANR  (grant  ANR-17-CE27-11 ), and the  ANR-DFG  (grant  ANR-18-FRAL-0006 ). 1 https: // doi. org /10. 1017/S0022226723000221  Published online by  Cambridge University.
Proceedings of the 15th International Conference on Archaeological Prospection ICAP 2023 Ferrex CON650, by Dr. Förster) was installed on a manual cart. The probes were mounted at intervals of 0. 5 m, so that each parallel profile covered a 2 m width. In-line, measurements were taken every 5 cm. The ERT mapping was carried out with the RESECS-Multielectrode-System. A total of 23 electrical profiles, each of them 32 m long, were measured with the configurations Dipole-Dipole and Wenner. The distance between electrodes and parallel profiles was of 1 m. The pseudosections were inverted in 2D using the open-source software BERT  (Günther and Rücker 2015). For the GPR, a single-channel instrument, SIR 4000 by GSSI, was used with a dual frequency antenna, including the main frequency bands of 300 MHz and 800 MHz.
Acknowledgments We like to thank  Şahan Kırçın , director of the  Edirne Museum , for extensive support during the field measurements. The project was funded by the  CNRS , through the project  LEGECARTAS -LEctures GEoarchéologiques des CARTes AncienneS  ( 2017-2019 ), and by the  French Ministry of Foreign Affairs -Mission Archéologique d'Ainos  ( 2020-present ).
Patterns in the NISP sample Because they provide the foundation of a large number of faunal interpretations, our comparisons begin with an analysis of the NISP sample (all layers are combined here to increase sample size, an analysis by layer is presented below). A chi-square test of independence shows no statistical difference in the taxonomic pro les produced by the two methods at all three sites (Crvena Stijena: χ 2 = 14. 0, p =. 1709; Saint-Césaire: χ 2 = 9. 7, p =. 2843; Le Piage: χ 2 = 3. 1, p =. 6801, Fig. 1 , data from Table  S1 ), an indication that the counts are not affected by the method of identi cation. Out of 26 pairwise comparisons of taxa, only one shows a taxonomic difference larger than 7% (reindeer at Saint-Césaire, difference of 10. 8% between the two methods, Table  S1 ).
Because errors may cancel one another in comparisons of whole samples, an additional test consists in determining if the morphological and ZooMS identi cations are consistent for the same specimen. In this case, we are ascertaining whether a given morphological identi cation-a Bos/Bison femur for instancematches the taxon given by ZooMS for the same specimen. The percentage of agreement, that is, the proportion of matches relative to the sum of compared specimens, is moderate at Saint-Césaire (69. 6%), whereas it is high at Crvena Stijena (91. 8%) and Le Piage (93. 2%, Table  3 ). A plot of the data suggests that errors of identi cation are more common when species are poorly represented, although the trend is not signi cant (r = 0. 69, p =. 0707, Fig. 2a , n > 4). The percentage of agreement in our dataset also seems inversely correlated with species diversity as measured by the reciprocal of Simpson's Index, a pattern that is observed regardless of whether the identi cations are based on the morphological or ZooMS counts (Fig.
Acknowledgments The authors would like to express their gratitude to  Aline Galland ,  Vasilije Marojevic  and  Đuro Pribilovic  for their humor and patience while processing the samples. Robert Whallon , who co-directed the earlier excavations at  Crvena Stijena  and supported our work, provided helpful comments on the draft. The faunal analysis at all three sites was supported by a  SSHRC Insight Grant  ( 435-2013-0993 ). The excavations at  Saint-Césaire  ( PCR La Roche-à-Pierrot ) are funded by the  Direction régionale des affaires culturelles of the Nouvelle-Aquitaine Region  and by the  Charente-Maritime Department, France , while those at  Le Piage  are made possible thanks to support received from the  Direction régionale des affaires culturelles of the Occitanie Region , also in France.
OM and SR-μ-XRPD highlighted in most cases a lower concentration of crystals in the upper part (50 μm) of the cross-sections (Figure  S7B ). This observation could explain why Švarcová et al. observed LF with XRPD in transmission mode but not in reflection and supports their hypothesis of the influence of particle sedimentation on the distribution of LF. The μ-FTIR map acquired on a thin section of cured PaDry succeeded in the detection of LF crystals, after non-negative matrix approx- imation calculations using the PyMCA ROI imaging software package  [17]  (Figure  S7C ). To further assess the relationship between the paint film thickness and the LF distribution, additional PaDry and PaWet films of controlled thickness (15, 30, 60 and 90 μm) were prepared using a paint applicator. Thin sections (10 μm) of these samples were analyzed with SR-μ-XRPD after four months of natural aging.
institutes has been and is supported by the Royal Netherlands Academy of Arts and Sciences, KNAW (Descartes-Huygens price 2018), and the PHC van Gogh granted by the French Ministries of European and Foreign Affairs, and of Higher Education, Research and Innovation. FWO (Brussels) is acknowledged for financial support under grant G054719N as well as Interreg Vlaanderen-Nederland via project Smart*Light and BELSPO (Brussels) for the FEDtWIN mandate Macro-Imaging. The main partner of Operation Night Watch is AkzoNobel. Operation Night Watch is made possible by The Bennink Foundation, C. L. de Carvalho-Heineken, PACCAR Foundation, Piet van der Slikke & Sandra Swelheim, American Express Foundation, Familie De Rooij, Het AutoBinck Fonds, TBRM Engineering Solutions, Dina & Kjell Johnsen, Familie D.
Acknowledgements The authors thank the entire  Operation Night Watch Team at the Rijksmuseum  for their help during MA-XRPD measurements, their expertise and constant support, particularly  E. Van Duijn  for her precious insights regarding the painting's conservation history, as well as  A. Krekeler  and  N. de Keyser  for their help with taking and preparing The Night Watch samples. We thank  M. Burghammer  ( ID13 ,  ESRF )  J. Garrevoet  ( P06 , DESY),  K. Ignatiev  ( I18 , DLS) and  N. Salvado  ( Universitat Politècnica de Catalunya ) for their support during the synchrotron experiments. We are indebted to  W. De Nolf  ( ESRF ) for help with the processing of SR data. We thank  S. Švarcová  at the  ALMA laboratory (Institute of Inorganic Chemistry of the Czech Academy of Sciences)  for providing us with a reference LF powder and for fruitful discussions.
IF thanks  J. Flapper  ( AkzoNobel ) and  B. de Bruin  ( UvA ) for their follow-up of the work. VG and IF have received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie actions  (Grant Agreement # 945298-ParisRegionFP  and  COFUND Programme "Inno-vaXN " #847439 respectively). This research was partially funded by the "3D understanding of degradation products in paintings" ( 3D2P ) project supported by the  Netherlands Institute for Conservation, Art and Science (NICAS)  and the  Dutch Research Council (NWO)  (project number  628. 007. 031 ). The ESRF beamtime was granted through the peer-reviewed BAG proposal HG-172 at ID13. The Historical materials BAG has been implemented with support from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  870313 ,  Streamline.
Participants A total of 263 people took part in the study (58. 3% women and 41. 3% men). Participants ranged in age from 18 to 71 years (M = 44. 1; SD = 12. 5), and 93. 1% were licenced drivers. Participants were recruited online, by publishing a post on several social network groups. Data was collected between March and April 2021, participants answered the questionnaire on Qualtrics. Participation was voluntary and free, all participants gave their consent to the analysis of their answers.
Participants To estimate the sample size needed for this study, we used the average effect size published in social psychology (d = 0. 43;  Richard et al. , 2003). Based on this effect size, the results obtained with G * Power indicates a sample size of at least 252 participants to achieve 80% power for an ANOVA analysis with 8 groups and 2 predictors (Format × Stage). 1  Participants were a total of 269 adults. Data was collected via online distribution of the digitised survey (on Qualtrics). After a preliminary examination of participants' responses, 11 participants were eliminated from further analyses. This was due to failure to correctly respond to the question "what colour is the blue sky, " leaving 258 responses for analysis. The final sample was composed of 38% men and 62% women, aged from 14 to 69 (M = 30.
Procedure Participants were recruited online, via a post published on social network groups not directly concerned with environmental protection. Data was collected between June and October 2021. After establishing informed consent, individuals were asked to indicate to which stage of behavioural change they were at with regards to pro-environmental behaviours (following the same procedure used in Study 1). Participants were randomly assigned to one of the two experimental message conditions. They were prompted to read their respective message and continue to answer a questionnaire. The measures were presented in the questionnaire the order in which they are described below (the questionnaire is reported in the section "Supplementary material"). Finally, participants were thanked and fully debriefed.
Classification of molecular operational taxonomic units (MOTUs) The nucleotide sequences obtained were edited in the MEGA7 program and aligned using the ClustalW tool  (Thompson et al. , 1994). For the distance analyses, we used a Neighbor-Joining  (Saitou and Nei, 1987)  algorithm with the Kimura-2 parameter model  (Kimura, 1980)  to estimate genetic distances. Robustness of nodes was evaluated through bootstrap re-analysis of 1000 pseudo-replicates. The tree was replotted using the online utility iTOL v4  (Letunic and Bork, 2019)  and the MOTUs were defined with the ABGD algorithm  (Puillandre et al. , 2012) , which is recognized as an efficient and reliable method for earthworm MOTU delineation on relatively small datasets  (Goulpeau et al. , 2022). The "barcode gap" was identified between intra-and interspecific distances.