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Artykuły w czasopismach na temat „PREDICTS”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Lluís, Xavier, Xavier Carreras, and Lluís Màrquez. "Joint Arc-factored Parsing of Syntactic and Semantic Dependencies." Transactions of the Association for Computational Linguistics 1 (December 2013): 219–30. http://dx.doi.org/10.1162/tacl_a_00222.

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In this paper we introduce a joint arc-factored model for syntactic and semantic dependency parsing. The semantic role labeler predicts the full syntactic paths that connect predicates with their arguments. This process is framed as a linear assignment task, which allows to control some well-formedness constraints. For the syntactic part, we define a standard arc-factored dependency model that predicts the full syntactic tree. Finally, we employ dual decomposition techniques to produce consistent syntactic and predicate-argument structures while searching over a large space of syntactic config

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2

Sreevidya, Nelli, K. Akshaya, Md Hamza, and T. Pranay. "Fire Prediction Analysis Based on Ensemble Machine Learning Algorithms." Asian Journal of Research in Computer Science 17, no. 6 (2024): 74–84. http://dx.doi.org/10.9734/ajrcos/2024/v17i6457.

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A fire accident is the most tragic incident in human life. Particularly environmental hazards such as forest fires lead loss of wildlife, economy, wealth, human lives and pollution. our research purpose of predict the occurrence of fire incidents using ensemble machine learning models. The goal is to develop an accurate and reliable model that can forecast the occurrence of forest fires based on various environmental factors. The best performance is obtained by the ensemble machine learning model for this work. Comparative study of individual model and ensemble model. If you check all models D

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3

Stoolmiller, Mike, and Elaine A. Blechman. "Substance Use is a Robust Predictor of Adolescent Recidivism." Criminal Justice and Behavior 32, no. 3 (2005): 302–28. http://dx.doi.org/10.1177/0093854804274372.

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How well does substance use predict adolescent recidivism? When the Cox proportional hazards model was applied to officially recorded first rearrest of 505 juvenile offenders, a best-fitting complex multivariate model indicated that: (a) parent reports that youths “often” use substances more than doubles first rearrest risk, (b) averaged youth and parent substance use reports predict recidivism better than a single source, (c) parent or youth denial of youth substance use predicts recidivism, (d) age at first arrest does not predict recidivism, (e) non-White/non-Asians have a 79% higher recidi

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4

Mostert, K., and B. Oosthuizen. "Job characteristics and coping strategies associated with negative and positive work-home interference in a nursing environment." South African Journal of Economic and Management Sciences 9, no. 4 (2014): 429–43. http://dx.doi.org/10.4102/sajems.v9i4.1032.

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The aim of this study is to determine which job characteristics and coping strategies predict negative and positive work-home interference (WHI) in the nursing environment. Random samples (n=300) were taken of registered nurses in the Johannesburg, Klerksdorp, Krugersdorp, Potchefstroom and Pretoria regions. A self-constructed questionnaire was used to measure job characteristics. The Coping Strategy Indicator (CSI) was used to measure coping strategies, and the Survey Work-Home Interaction-Nijmegen (SWING) to measure WHI. The results show that time demands, pressure, role clarity and colleagu

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5

Floriddia, Elisa. "Transcriptomics predicts activity." Nature Neuroscience 25, no. 8 (2022): 977. http://dx.doi.org/10.1038/s41593-022-01144-z.

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6

Carstensen, Earl J. "BMI Predicts Mortality." Physician and Sportsmedicine 32, no. 1 (2004): 38. http://dx.doi.org/10.3810/psm.2004.01.74.

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7

Holman, Thomas B., and John Gottman. "What Predicts Divorce?" Family Relations 44, no. 1 (1995): 116. http://dx.doi.org/10.2307/584749.

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8

Holding, Cathy. "Ploidy predicts lifestyle." Genome Biology 5 (2004): spotlight—20040714–01. http://dx.doi.org/10.1186/gb-spotlight-20040714-01.

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9

Denny, Kevin. "Breastfeeding predicts handedness." Laterality: Asymmetries of Body, Brain and Cognition 17, no. 3 (2012): 361–68. http://dx.doi.org/10.1080/1357650x.2011.579131.

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10

Alex Tullo. "Moody’s predicts upturn." C&EN Global Enterprise 101, no. 12 (2023): 10. http://dx.doi.org/10.1021/cen-10112-buscon6.

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11

Moore, Simon C., and James Foreman-Peck. "Alcohol Consumption Predicts Violent Victimization, Impulsive Decision Making Predicts Violence." Open Behavioral Science Journal 3, no. 1 (2009): 28–33. http://dx.doi.org/10.2174/1874230000903010028.

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12

Nuñez, Martin A., and Kim A. Medley. "Pine invasions: climate predicts invasion success; something else predicts failure." Diversity and Distributions 17, no. 4 (2011): 703–13. http://dx.doi.org/10.1111/j.1472-4642.2011.00772.x.

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13

Slepian, Michael L., and James N. Kirby. "To Whom Do We Confide Our Secrets?" Personality and Social Psychology Bulletin 44, no. 7 (2018): 1008–23. http://dx.doi.org/10.1177/0146167218756032.

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Although prior work has examined secret keeping, no prior work has examined who gets told secrets. Five studies find compassion and assertiveness predict having secrets confided in oneself (as determined by both self- and peer reports), whereas enthusiasm and politeness were associated with having fewer secrets confided. These results bolster suggestions that interpersonal aspects of personality (which can fit a circumplex structure) are driven by distinct causal forces. While both related to agreeableness, compassion (empathy and desire to help) predicts being confided in more, whereas polite

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14

Slepian, Michael L., and Edythe Moulton-Tetlock. "Confiding Secrets and Well-Being." Social Psychological and Personality Science 10, no. 4 (2018): 472–84. http://dx.doi.org/10.1177/1948550618765069.

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How does confiding secrets relate to well-being? The current work presents the first empirical examination of mechanisms by which confiding diverse real-world secrets to known others predicts well-being. We examined over 800 participants with more than 10,000 secrets in total, finding that confiding a secret does not predict reduced instances of concealment. Rather, confiding a secret predicts higher well-being through perceived coping efficacy. Correlational and experimental studies find that through confiding a secret, people feel they obtain social support and are more capable in coping wit

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15

Patterson, M. C. "Holoprosencephaly: The face predicts the brain; the image predicts its function." Neurology 59, no. 12 (2002): 1833–34. http://dx.doi.org/10.1212/wnl.59.12.1833.

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16

Sisco, Shannon M., and Michael Marsiske. "Neighborhood Influences on Late Life Cognition in the ACTIVE Study." Journal of Aging Research 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/435826.

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Low neighborhood-level socioeconomic status has been associated with poorer health, reduced physical activity, increased psychological stress, and less neighborhood-based social support. These outcomes are correlates of late life cognition, but few studies have specifically investigated the neighborhood as a unique source of explanatory variance in cognitive aging. This study supplemented baseline cognitive data from the ACTIVE (Advanced Cognitive Training for Independent and Vital Elderly) study with neighborhood-level data to investigate (1) whether neighborhood socioeconomic position (SEP)

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17

Hendershott, Terrence, Roman Kozhan, and Vikas Raman. "Short Selling and Price Discovery in Corporate Bonds." Journal of Financial and Quantitative Analysis 55, no. 1 (2018): 77–115. http://dx.doi.org/10.1017/s0022109018001539.

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We show short selling in corporate bonds forecasts future bond returns. Short selling predicts bond returns where private information is more likely, in high-yield bonds, particularly after Lehman Brothers’ collapse of 2008. Short selling predicts returns following both high and low past bond returns. This, together with short selling increasing following past buying order imbalances, suggests short sellers trade against price pressures as well as trade on information. Short selling predicts bond returns both in the individual bonds that are shorted and in other bonds by the same issuer. Past

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18

Kim, N. H., B. Youn, and R. L. Webb. "Air-Side Heat Transfer and Friction Correlations for Plain Fin-and-Tube Heat Exchangers With Staggered Tube Arrangements." Journal of Heat Transfer 121, no. 3 (1999): 662–67. http://dx.doi.org/10.1115/1.2826030.

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This paper deals with heat exchangers having plain fins on a staggered array of circular tubes. Correlations are developed to predict the air-side heat transfer coefficient and friction factor as a function of the Reynolds number and geometric variables of the heat exchanger such as tube diameter, tube pitch, fin spacing, etc. A multiple regression technique was used to correlate 47 sets of heat exchanger data to develop the heat transfer and friction correlation. The correlations are applicable to heat exchangers having small diameter tubes (or large tube pitch to tube diameter ratio), whose

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19

Braun, Michael T., Steve W. J. Kozlowski, Tara A. (Rench) Brown, and Richard P. DeShon. "Exploring the Dynamic Team Cohesion–Performance and Coordination–Performance Relationships of Newly Formed Teams." Small Group Research 51, no. 5 (2020): 551–80. http://dx.doi.org/10.1177/1046496420907157.

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Emergent states, like cohesion, and behavioral processes, like coordination, are considered critical for team performance, yet little is known regarding their relative importance over time. Testing several hypotheses and exploring multiple research questions, this study used a laboratory design to better understand the evolution of cohesion–performance and coordination–performance relationships of newly formed teams. Forty-two teams of three completed 10 task episodes of an interdependent team task over the course of two and a half hours. Results reveal that cohesion and performance have a rec

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20

Johansson, Alva, Niclas Berggren, and Therese Nilsson. "Intolerance predicts climate skepticism." Energy Economics 105 (January 2022): 105719. http://dx.doi.org/10.1016/j.eneco.2021.105719.

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21

Royall, Donald R., та Raymond F. Palmer. "δ PREDICTS GENERAL PSYCHOPATHOLOGY". Innovation in Aging 3, Supplement_1 (2019): S639. http://dx.doi.org/10.1093/geroni/igz038.2378.

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Abstract “δ” is a transdiagnostic omnibus dementia severity measure derived from general intelligence (i.e., Spearman’s “g”). It can be estimated in any cognitive battery that contains a measure of Instrumental Activities of Daily Living (IADL). As dementia’s essential cognitive impairment, δ may also explain the appearance of Behavioral and Psychological Symptoms of Dementia (BPSD). Alternatively, the latter may be associated with orthogonal domain-specific cognitive impairments, unrelated to δ and therefore to dementia. The δ homolog ”dDx” was tested as a predictor of one year prospective BP

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22

Sidaway, Peter. "MHC expression predicts response." Nature Reviews Clinical Oncology 15, no. 10 (2018): 591. http://dx.doi.org/10.1038/s41571-018-0082-3.

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23

Cole, J. H., S. J. Ritchie, M. E. Bastin, et al. "Brain age predicts mortality." Molecular Psychiatry 23, no. 5 (2017): 1385–92. http://dx.doi.org/10.1038/mp.2017.62.

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24

Carr, Fiona. "Visual fixation predicts function." Nature Reviews Neuroscience 16, no. 5 (2015): 248. http://dx.doi.org/10.1038/nrn3959.

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25

Carney, Ellen F. "Podocyturia predicts pre-eclampsia." Nature Reviews Nephrology 9, no. 6 (2013): 310. http://dx.doi.org/10.1038/nrneph.2013.72.

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26

Martin, Dawn Lundy. "What the Memory Predicts." Callaloo 24, no. 3 (2001): 830–31. http://dx.doi.org/10.1353/cal.2001.0179.

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27

Zinke, Laura. "Fickle fall predicts flu." Nature Reviews Earth & Environment 1, no. 3 (2020): 138. http://dx.doi.org/10.1038/s43017-020-0036-z.

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28

&NA;. "What predicts placebo response?" Inpharma Weekly &NA;, no. 852 (1992): 19. http://dx.doi.org/10.2165/00128413-199208520-00036.

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29

Stillman, Paul E., and Melissa J. Ferguson. "Decisional Conflict Predicts Impatience." Journal of the Association for Consumer Research 4, no. 1 (2019): 47–56. http://dx.doi.org/10.1086/700842.

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30

Yehezkel, O., A. Sterkin, M. Lev, and U. Polat. "Crowding predicts reading abilities." Journal of Vision 14, no. 10 (2014): 785. http://dx.doi.org/10.1167/14.10.785.

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31

Green, David, Nancy Foiles, Cheeling Chan, Pamela J. Schreiner, David Jacobs, and Kiang Liu. "Elevated Fibrinogen Predicts Atherosclerosis." Blood 110, no. 11 (2007): 3188. http://dx.doi.org/10.1182/blood.v110.11.3188.3188.

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Abstract Elevated levels of hemostatic factors are observed in patients with atherosclerosis, but whether they promote plaque formation or are a consequence of the disease is uncertain. To examine this issue, we used data from a large biracial cohort of young adults (Coronary Artery Risk Development in Young Adults [CARDIA]) followed up for 13 years, to examine the relationships of hemostatic factors - fibrinogen, factors VII and VIII, and von Willebrand factor (vWF) - with coronary artery calcium (CAC) and carotid intimal-medial thickness (IMT). Complete data were available on 1382 participan

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32

Meier, Stephan, and Charles D. Sprenger. "Time Discounting Predicts Creditworthiness." Psychological Science 23, no. 1 (2011): 56–58. http://dx.doi.org/10.1177/0956797611425931.

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33

Stirrat, M., and D. I. Perrett. "Face Structure Predicts Cooperation." Psychological Science 23, no. 7 (2012): 718–22. http://dx.doi.org/10.1177/0956797611435133.

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34

Laura Howes. "AI predicts protein structures." C&EN Global Enterprise 98, no. 47 (2020): 4. http://dx.doi.org/10.1021/cen-09847-leadcon.

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35

Greenberg, David M., Daniel Müllensiefen, Michael E. Lamb, and Peter J. Rentfrow. "Personality predicts musical sophistication." Journal of Research in Personality 58 (October 2015): 154–58. http://dx.doi.org/10.1016/j.jrp.2015.06.002.

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36

Turk, Victoria. "AI predicts the future." New Scientist 232, no. 3102 (2016): 22. http://dx.doi.org/10.1016/s0262-4079(16)32228-x.

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37

Cuestas, Eduardo, Alina Rizzotti, and Guillermo Agüero. "Heart rate predicts sepsis." Journal of Pediatrics 161, no. 4 (2012): 770. http://dx.doi.org/10.1016/j.jpeds.2012.07.001.

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38

Cook, Emily, Stephen T. Hammett, and Jonas Larsson. "GABA predicts visual intelligence." Neuroscience Letters 632 (October 2016): 50–54. http://dx.doi.org/10.1016/j.neulet.2016.07.053.

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39

STORCK, WILLIAM. "Pfizer Predicts Earnings Growth." Chemical & Engineering News 79, no. 52 (2001): 6. http://dx.doi.org/10.1021/cen-v079n052.p006a.

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40

Henderson, J. "Facial attractiveness predicts longevity." Evolution and Human Behavior 24, no. 5 (2003): 351–56. http://dx.doi.org/10.1016/s1090-5138(03)00036-9.

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41

Sullivan, Michele G. "Brain Atrophy Predicts Decline." Caring for the Ages 15, no. 3 (2014): 5. http://dx.doi.org/10.1016/j.carage.2014.02.007.

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42

Terhune, D. B., S. Russo, J. Near, C. J. Stagg, and R. Cohen Kadosh. "GABA Predicts Time Perception." Journal of Neuroscience 34, no. 12 (2014): 4364–70. http://dx.doi.org/10.1523/jneurosci.3972-13.2014.

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43

Lobato, Emilio J. C., Shadab Tabatabaeian, Morgan Fleming, Sven Sulzmann, and Colin Holbrook. "Religiosity Predicts Evidentiary Standards." Social Psychological and Personality Science 11, no. 4 (2019): 546–51. http://dx.doi.org/10.1177/1948550619869613.

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Research shows that religious and nonreligious individuals have different standards of evidence for religious and scientific claims. Here, in a preregistered replication and extension of McPhetres and Zuckerman, participants read about an effect attributed to either a scientific or religious cause, then assessed how much evidence, in the form of successful replications, would be needed to confirm or to reject the causal claim. As previously observed, religious individuals exhibited a bias for believing religious claims relative to scientific claims, while nonreligious individuals were consiste

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44

Stone, Louise. "AXL expression predicts prognosis." Nature Reviews Urology 14, no. 12 (2017): 700. http://dx.doi.org/10.1038/nrurol.2017.186.

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45

Thoma, Clemens. "Lineage predicts ADT response." Nature Reviews Urology 14, no. 8 (2017): 450. http://dx.doi.org/10.1038/nrurol.2017.80.

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46

Wiederhold, Brenda K. "What Predicts Facebook Addiction?" Cyberpsychology, Behavior, and Social Networking 20, no. 5 (2017): 277. http://dx.doi.org/10.1089/cyber.2017.29073.bkw.

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47

Finn, Robert. "Metabolic Syndrome Predicts Frailty." Caring for the Ages 7, no. 1 (2006): 24. http://dx.doi.org/10.1016/s1526-4114(06)60015-2.

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48

Kriebs, Anna. "Skin autofluorescence predicts T2DM." Nature Reviews Endocrinology 15, no. 2 (2018): 64. http://dx.doi.org/10.1038/s41574-018-0141-y.

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Berces, Katalin Balogne, and Balint Huszthy. "Laryngeal Relativism predicts Italian." Yearbook of the Poznan Linguistic Meeting 4, no. 1 (2018): 153–77. http://dx.doi.org/10.2478/yplm-2018-0007.

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Abstract Two-way laryngeal systems are classified by Laryngeal Realism into [voice] languages (or “L-systems”, e.g., Slavic, Romance) and [spread glottis] ([sg]; or aspiration) languages (or “H-systems”, e.g., the typical Germanic pattern). More recently, Cyran (2014) has proposed Laryngeal Relativism (LR), claiming that phonetic interpretation is arbitrary, and as a result, two phonetically identical systems, even two dialects of a language, may turn out to diverge phonologically. His example is Polish: while Warsaw Polish represents the typical [voice]/L-system, he analyses phonetically iden

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50

&NA;. "Erectile dysfunction predicts CVD." Nursing 38, no. 8 (2008): 25–26. http://dx.doi.org/10.1097/01.nurse.0000327482.55322.c3.

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