dataesr/scientific-paragraphs-categorization huggingface dataset:
3 ). This basic structure gave rise to a continuous stream of strictly alternating frequent (A and B) and infrequent (X and Y) words, mimicking function words and content words, respectively. The initial and final 15 s of the stream were ramped in amplitude in order to mask any phase information. The familiarization stream was thus ambiguous between a frequent word initial or FI (for example, AXBY) and a frequent word final or IF (for example, XBYA) parse. The familiarization stream was synthesized using the fr4 female diphone database of MBROLA  31. In the OV prosody condition of Experiments 1 and 2, we used high pitch (224 Hz) on the prominent infrequent words and low pitch (200 Hz) on the non-prominent frequent words, both with a constant phoneme duration of 120 ms. In the VO prosody condition of Experiment 1, the prominent infrequent words were long (144 ms), the non-prominent frequent words were short (120 ms), and both had a constant pitch of 200 Hz.
Acknowledgements This work was supported by grants from the  McDonnell Foundation  ( 220020096 ), the  Social Sciences and Humanities Research Council of Canada  ( 28233 ), and the  Natural Sciences and Engineering Research Council of Canada  ( 81103 ) to  Janet Werker  and from the  Agence Nationale de la Recherche  ( Programme JC 21373 ) and the  Fyssen Foundation  to  Judit Gervain. We would like to thank  Nayeli Gonzalez Gomez ,  Neda RazazRahmati  and  Mark Scott  for their help with the prosodic analyses,  Alison Greuel ,  Maria Lenart  and  Jing Guo  for their help with infant testing, and  Marina Nespor ,  Jacques Mehler ,  Laurel Fais ,  Krista Byers-Heinlein  and  Henny H Yeung  for valuable discussions and their feedback on previous versions of the manuscript.
Study population Analyses were based on data of the IDEFICS (identification and prevention of dietary-and lifestyle-induced health effects in children and infants) study, which is the largest European multicenter study to date, aiming to investigate the causes and consequences of overweight and obesity in 2-to 9-year-old children. The IDEFICS baseline survey enrolled 16,864 children (response rate 53. 4 %), 16,225 (51. 4 %) of whom fulfilled the inclusion criteria (complete information on age, sex, height and weight). The baseline survey was conducted in eight European countries (Sweden, Germany, Hungary, Italy, Cyprus, Spain, Belgium and Estonia) from September 2007 to May 2008. Sampling and basic study characteristics have been described elsewhere  [17]. In each country, participating centers obtained ethical approval from the local responsible authorities in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
For harmonization, all energy and nutrient data of the countryspecific FCT were expressed in 100 g standard portion per food 'as consumed. ' Standard units were taken from McCance and Widdowson's  [32]. Finally, total energy content was calculated in kcal. The proxies, mainly the parents, were assisted by trained survey personnel or the dietician from the survey team when completing the 24HDR. The required time frame for one interview was 20-30 min  [22]. The validity of proxy-reported energy intake from the 24HDR was tested using the doubly labeled water technique in young children. The instrument was found to be valid to assess energy intake on group level  [33].
Data cleaning Multiple steps of data cleaning assured data quality since not only recall and reporting bias, but also erroneous data entry, incorrect coding and false standard amounts could have resulted in missing and implausible data. Missing quantities or implausible values (above median ? 2. 5 standard deviation or intakes of [1,500 ml (gastric capacity)  [34]  for single food items) that could not be corrected were imputed by country, food group and agespecific median intakes (0. 01 % of the entries). Incomplete 24HDR and 24HDR with four or more imputed values were excluded from the analysis. From the full survey sample of 16,225 children, subjects with one complete 24HDR and covariate information required were included in the study final analysis (N = 9,782). No significant differences were observed between survey and study sample characteristics such as age, gender, weight status, educational level of parents and energy reporting.
Data analysis Consistency of proxy-reported energy intake with energy requirements was estimated using the ratio of proxyreported energy intake over predicted basal metabolic rate  [35]. This was calculated to classify all individuals with underreported energy intake, plausible reported energy intake and overreported energy intake according to adapted Goldberg cutoffs  [36]. Goldberg cutoff values were recalculated for application in children  [37]  using age-and sexspecific reference values. The following eating habit parameters were investigated: total daily energy intake (1 unit * 100 kcal of total daily intake), total daily food intake and drinks (1 unit * 100 g of total daily food intake) and total energy intake (kcal/day) divided by total daily food intake (g/day). Parameters were calculated in 100 g or 100 kcal units since we did not expect relevant effects on BMI z-score of 1 g or 1 kcal units.
Since energy intake and daily food intake are highly interrelated, their predictive power on BMI z-score was tested in a combined model including an additional interaction term. All models were adjusted for age and sex of the child and maximum educational level of both parents according to International Standard Classification of Education (IS-CED). ISCED level was used as proxy indicator for socioeconomic status (SES) of the family. To account for clustered study design, a random effect was added for the study center. Statistical significance was set at P B 0. 01. All statistical analyses were performed using SAS 9. 2 (SAS Institute, Cary, NC, USA).
Descriptive statistics Approximately 21 % of the study population was overweight or obese, with a higher prevalence among school children (26 %) than preschool children (15 %) (Table  1 ). The study sample included the highest proportion (20 %) of dietary data from Italian children and the lowest (4 %) from Belgian children. In total, 87 % (N = 8,544) of the 24HDRs were classified as plausible energy reports. The mean daily energy intake was 1,511 kcal in the full sample (N = 9,782) and 1,547 kcal in the plausible energy reporting subsample (Table  2 ). The average daily food intake (excluding noncaloric beverages) was 1,213 g in the full sample and 1,247 g in the plausible energy reporting subsample. The daily energy density of foods was 1. 3 kcal/g in both samples. In the plausible energy reports, subsample mean daily energy intake was 1,520 kcal among the thin/normal weight children and 1,660 kcal among overweight/obese children.
However, reverse causality has to be taken into account when interpreting cross-sectional associations. The validity of future analyses of the IDEFICS longitudinal data will possibly be less affected by such bias. Energy intake may be influenced by the energy density (kcal/g) of foods and beverages  [13]. The calculation of energy density of foods strongly differs between studies and can be based on all foods consumed. Drinking water or even all kind of beverages is generally excluded. In the present study, daily food intake and energy density of foods included foods and energy-containing beverages since satiation studies have shown that humans tend to consume a constant amount of foods by weight or volume on a dayto-day basis  [13]. Although an association between energy density of foods, excluding beverages and water, and body weight was observed in very recent publications  [40, 41] , we did not exclude energy-containing beverages since they contribute increasingly to the daily energy intake, e.
Excess body weight is the result of an imbalance between energy intake and total energy expenditure  [56]. Physical activity may therefore confound associations between eating habit variables and BMI z-score. Hence, we adjusted for proxy-reported physical activity (total daily duration of outdoor playing in minutes) in preliminary analyses (data not shown). The validity of proxy-reported physical activity data was, however, considered questionable as it was positively associated with the BMI z-score in all regression models. The estimate for the exposure variables changed only marginally while the significance remained unchanged; thus, we decided not to include the physical activity variable in the regression models. In general, validity and reliability of proxy-reported physical activity have been observed to be low for questionnaire surveys in youth  [57].
Conclusion The IDEFICS study is the first study to investigate the association between proxy-reported daily food intake, energy intake and energy density of foods and BMI z-score in 2-9-year-old European children. The results indicate that proxy-reporters are subject to misreporting especially for children in the higher BMI levels and that energy intake is a more important predictor of unhealthy weight development in children than daily food intake. The promotion of age-appropriate energy intake should therefore be emphasized in the prevention of overweight among children. We advise that future investigations focus on the effects of energy intake and energy density of foods on weight development, preferably in a longitudinal data set.
Acknowledgments We gratefully acknowledge the support provided by school boards, headmasters and communities. We thank the IDEFICS children and their parents for participating in this extensive examination. We further greatly appreciate the valuable input of Hermann Pohlabeln. This work was done as part of the IDEFICS study (www. idefics. eu)and is published on behalf of its European Consortium. We gratefully acknowledge the financial support of the  European Community  within the  Sixth RTD Framework Programme  Contract No. 016181  (FOOD). The information in this document reflects the author's view and is provided as is.
Location sensitivity across training epochs Figure  4  shows the average evolution of recognition accuracy and location sensitivity in 10 networks, as assessed at 20 epochs of training (to be called steps hereafter, referring to steps rather than directly to epochs is necessary given that networks needed different numbers of epochs to reach criterion: if network X took longer to train than network Y, one training step for X contains more epochs than one training step for Y). At each step location sensitivity was measured just as before, by the generalization    performance of a linear classifier on sorting 40 randomly chosen hidden network patterns into 2 or 6 location classes. Two aspects of the data are immediately obvious. First, before training (step 0) networks have as expected no recognition ability, but nonetheless they already exhibit location sensitive hidden representations, a sensitivity which peaks after the first weight modifications.
Captured by the "less is more" hypothesis, Newport  (Newport, 1990; Goldowsky and Newport, 1993)  argues that infants tend to rely more heavily on rule extraction and regularization, because their memory capacity, more limited than that of adults, prevents them from memorizing large data sets item by item. Given limited memory, the most efficient way to encode and learn a dataset is to extract regularities. Adults, not limited by memory constraints in the same way, might rely more on memorizing, item-based or statistical learning instead. Indeed, late learners of a language have been observed to memorize entire unanalyzed chunks or sequences, which young learners tend to decompose instead (e. g. , for American Sign Language;  Newport, 1984). Similarly, experiments testing how faithfully younger and older learners encode morphosyntactic properties that appear probabilistically or inconsistently in the input found that children were more likely to regularize inconsistencies, while adults only did so for the most inconsistent features  (Hudson Kam and Newport, 2009).
Corpora We used corpora from four languages. In Japanese, Italian, and French, transcriptions of actual speech directed to infants and young children were available. For Basque, currently no such database exists. We, therefore, used a variety of written sources, mainly texts extracted from newspapers as well as children's books. The four languages we examined have different orthographic traditions. In Japanese, for example, postpositions are written as separate words, while in Basque, they are attached to the noun. To eliminate such differences, agglutinative affixes (i. e. , elements of inflectional morphology attaching to the word stem, e. g. , Basque mendi-tik mountain from) were encoded as separate morphemes 4. Thus, the corpora were tagged and segmented into morphemes. This allowed us to take both free and bound functors into account, better reflecting adult speakers' full-fledged (but, of course, implicit) knowledge of their native grammar.
The corpora were phonologically transcribed to provide a more realistic signal using phonotypical pronunciations in a semi-automated manner  (Roach et al. , 1996). For each language, we collected 10 subcorpora from independent sources, i. e. , different speakers or different texts, in order to have independent data points for each language, allowing statistical analysis. Each subcorpus in each language comprised 500 utterances, for a total of 5000 utterances per language. We relied on the original corpora for the definition of utterances. We counted as a single utterance whatever was transcribed as such in the original corpora. Equating the number of utterances per subcorpus and per language allowed us to better compare languages and to control for potential biases resulting from sample size and data sparsity, which might affect linguistic variability and frequency counts, at least for medium or low frequency linguistic features  (Biber and Finegan, 1991; De Haan, 1992).
, 1989; Tonelli et al. , 1995; Salerni et al. , 2007)  of the CHILDES database  (MacWhinney, 2000). The full corpus comprises 5000 utterances. For French, we used 500utterance-long samples of the speech of 10 adults from the Paris subcorpus  (Morgenstern and Parisse, 2007; Leroy et al. , 2009; Morgenstern and Sekali, 2009)  of the CHILDES database. The resulting full corpus consists of 5000 utterances.
We identified the first and the last two items of utterances, i. e. , bimorphemic "phrases" at the left and right utterance boundaries. If the "phrase" had a [frequent item-infrequent item] order, it was counted as FI. Examples of FI phrases include è rosso is red "(it) is red," all' asilo in-the daycare "in the daycare" [Italian, presented orthographically for ease of exposition]. If it had an [infrequent item-frequent item] structure, it was counted as IF. Examples of IF phrases include zoritxar haren misfortune his "his bad luck"  [Basque]. "Phrases" where both morphemes were of the same category, i. e. , [frequent item-frequent item] or [infrequent item-infrequent item] did not enter into the counts 7. For statistical purposes, we calculated the proportion of FI and IF utterances in each subcorpus in the above defined way, and conducted analyses of variance over the obtained datasets.
018] due to the greater number of IF phrases in the overall dataset, just like in the first ANOVA. Again, the interaction between Language and Order was significant [F (1, 36) = 20. 07, p < 0. 0001]. In Scheffe post-hoc tests, we found significant differences between the number of IF and FI items in Basque (p < 0. 0001) and in Japanese (p < 0. 001), marginally so in Italian (p = 0. 07) and not in French. Further, although numerically, the number of IF phrases was greater in Basque than in Japanese, this difference did not reach significance.
These manipulations created a continuous artificial grammar similar to the one used in  Gervain et al. (2008) , with the only difference that in the current study three rather than two frequent and infrequent categories were used in order to make the material more suitable for adults. Care was taken to avoid phonotactic and frequency biases (i) by avoiding phoneme sequences that are illegal or infrequent in one or more of the languages and (ii) by matching the frequencies of syllables used in the initial positions of test items across the four languages 8. All 36 syllables used to create the stream were chosen to have similar frequencies in word initial positions in Japanese, Italian, Basque, and French. The familiarization stream was synthesized using the es1 Spanish male diphone database of MBROLA  (Dutoit, 1997) , with a monotonous pitch of 100 Hz and a constant phoneme duration of 120 ms.
After training, participants were instructed to listen to the familiarization stream, which lasted 17 min 30 s. After familiarization, participants passed immediately onto the test phase. In each of the 36 trials, they heard a pair of "sentences," and they had to indicate by pressing one of two predefined keys which of the two "sentences" sounded more like a possible sentence of the unknown language. Items within a pair were separated by a pause of 500 ms. The computer recorded the number of IF responses, which was used for data analysis. The number of FI responses can be obtained by subtracting this number from the total number of trials (36). Basque participants were tested in the Psycholinguistics Laboratory of the University of the Basque Country, Vitoria-Gasteiz, Spain in collaboration with the Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.
ACKNOWLEDGMENTS This work was supported by grants from the  Agence Nationale de la Recherche  ( Programme JC 21373 ), the  Fyssen Foundation  and the  Emergence(s) program of the City of Paris  to  Judit Gervain , the  ESF Eurocores OMLL  grant and the  Italian National Grants (COFIN)   2003-2007  to  Marina Nespor , a  James S. McDonnell Foundation  grant to  Jacques Mehler , the  European Research Council  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013)  /  ERC  grant agreement n • 269502 (PASCAL), to  Jacques Mehler , and the  Spanish Ministerio de Ciencia e Innovación  ( PSI2012-34071  to  Núria Sebastián-Gallés ;  FFI2012-31360  (and  Basque Government   IT665-13 ) to Itziar Laka, Consolider-Ingenio  2010-CDS-2007-00012  to  Núria Sebastián-Gallés  and  Itziar Laka ), Grants- In-Aid for Scientific Research  by  Japanese Ministry of Education, Culture and Sports  to  Reiko Mazuka  (Kakenhi No.
21610028 ), and the  People Programme  ( Marie Curie Actions ) of the European Union's  Seventh Framework Programme  ( FP7/2007-2013)  under  REA  grant agreement n  • 328671  to  Begoña Díaz. Núria Sebastián-Gallés  received the prize " ICREA Acadèmia"  for excellence in research, funded by the  Generalitat de Catalunya. We would like to thank  Emmanuel Dupoux ,  Franck Ramus  and other members of the  Laboratoire de Science Cognitive et Psycholinguistique (EHESS-CNRS-ENS, Paris, France)  for allowing us to use their facilities to test the French participants. We are grateful to  Krista Byers-Heinlein ,  Laurel Fais ,  Mark Scott ,  Katie Yoshida ,  Whitney Weikum , and  Janet Werker  for their comments on earlier versions of the paper.
Method Ethics statement. Parents of all infant participants provided written informed consent prior to the experiment. The experimental protocol and consent procedure were both approved by the CERES (Comité d'évaluation éthique des projets de recherche) of the Université Paris Descartes. All data were obtained according to the principles expressed in the Declaration of Helsinki. Participants. Twenty 8-month-old infants (mean age: 8. 3 months; range: 7. 8-8. 8 months) from French-speaking families were tested (9 females and 11 males). Data from four additional infants were excluded from the analysis due to fussiness (3) or due to a segmentation index (defined as the difference between the mean orientation times to the lists of target and control syllables) more than 2 SDs above or below the group mean  (1).
All infants were full term, had no major problem during pregnancy and birth and had normal development and hearing. Their parents had neither hearing impairment nor language problems. The infants were recruited through birth lists from the Paris area and parents gave a written informed consent. Stimuli. As done in previous research on this topic, we selected stimuli with relatively low frequencies, using the adult database LEXIQUE  [54]  (given per 1 million occurrences, and calculated over a base of 31 million occurrences). We selected four syllables with relatively low frequencies in the initial and final positions of French words: /ba/ (initial position: 5. 99; final position: 14. 12); /di/ (initial position: 16. 10; final position: 5. 94); /pu/ (initial position: 5. 19; final position:.
Method Participants. Twenty 8-month-old infants (mean age: 8. 2 months; range: 7. 7-8. 7 months) from French-speaking families were tested (13 females and 7 males). Data from four additional infants were excluded from the analysis due to fussiness (4). Infants were recruited following the same procedure and criteria as in Experiment 1. Stimuli. The familiarization stimuli were the same passages as in Experiment 1. The pair of target words in the passages had an average duration of 340 ms. Their mean intensity was 71 dB, and their mean pitch was 232 Hz. The female talker of Experiment 1 had also recorded four lists of 20 alternating target words, again as if speaking to an infant, and with some variation, one for each target syllable, which were used in the present test phase. The duration of each list was 20 s and the words were separated by a mean ISI of 560 ms.
Method Participants. Twenty 8-month-old infants (mean age: 8. 3 months; range: 7. 9-9. 2 months) from French-speaking families were tested (7 females and 13 males). Data from one additional infant were excluded from the analysis due to fussiness. Infants were recruited following the same procedure and criteria as in Experiments 1 and 2. Stimuli. In this experiment, three of the four syllables chosen as stimuli differed from the ones used in Experiment 1 because eight relatively low frequency words per syllable needed to be selected, and this was only possible for one of the syllables used in Experiment 1. Therefore, we again used Lexique  [54]  to select four syllables with relatively low frequencies (again given per 1 million of occurrences) in initial and final positions of French words: /di/ (initial position: 11.
For example, LAMS  (Learning Activity Management System: Dalziel 2003)  facilitates the micro-level planning and automation of the learning activities, whereas the Learning Designer  (Laurillard et al. 2013)  facilitates design work at the macro level, aiding the design of whole learning sessions and modules, and supporting more strategic pedagogical thinking. These different foci of support require different visual representations to abstract the individual elements of a design such as learning activities and resources, so that they can be easily defined and manipulated. As the number of learning design authoring tools continues to grow, it becomes increasingly difficult to keep track of them or to engage with each one in depth. Few researchers or practitioners have the time to try multiple tools or to compare how different tools model a particular learning scenario in order to see which one best suits their needs.