R: A Language and Environment for Statistical Computing

Differences in genetic and environmental influences on the human cerebral cortex associated with development during childhood and adolescence

Lenroot, R. K., Schmitt, J. E., Ordaz, S. J., Wallace, G. L., Neale, M. C., Lerch, J. P., Kendler, K. S., Evans, A. C., & Giedd, J. N. (2009) · Human Brain Mapping · doi:10.1002/hbm.20494 · Cited by 320

Associations between rejection sensitivity and mental health outcomes: A meta-analytic review

Gao, S., Assink, M., Cipriani, A., & Lin, K. (2017) · Clinical Psychology Review · doi:10.1016/j.cpr.2017.08.007 · Cited by 330

Clearance of senescent decidual cells by uterine natural killer cells in cycling human endometrium

Brighton, P. J., Maruyama, Y., Fishwick, K., Vrljicak, P., Tewary, S., Fujihara, R., Muter, J., Lucas, E. S., Yamada, T., Woods, L., et al. (2017) · eLife · doi:10.7554/elife.31274 · Cited by 323

Biochar mitigates negative effects of salt additions on two herbaceous plant species

Thomas, S. C., Frye, S., Gale, N., Garmon, M., Launchbury, R., Machado, N., Melamed, S., Murray, J., Petroff, A., & Winsborough, C. (2013) · Journal of Environmental Management · doi:10.1016/j.jenvman.2013.05.057 · Cited by 333

Don't let spurious accusations of pseudoreplication limit our ability to learn from natural experiments (and other messy kinds of ecological monitoring)

Davies, G. M., & Gray, A. (2015) · Ecology and Evolution · doi:10.1002/ece3.1782 · Cited by 333

Global Proteome Analysis of the NCI-60 Cell Line Panel

Gholami, A. M., Hahne, H., Wu, Z., Auer, F. J., Meng, C., Wilhelm, M., & Kuster, B. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.07.018 · Cited by 302

What determines a species' geographical range? Thermal biology and latitudinal range size relationships in European diving beetles (Coleoptera: Dytiscidae)

Calosi, P., Bilton, D. T., Spicer, J. I., Votier, S. C., & Atfield, A. (2010) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2009.01611.x · Cited by 332

Rational irrationality: modeling climate change belief polarization using Bayesian networks

Cook, J., & Lewandowsky, S. (2016) · Topics in Cognitive Science · doi:10.1111/tops.12186 · Cited by 332

Four Centuries of Change in Northeastern United States Forests

Thompson, J. R., Carpenter, D. N., Cogbill, C. V., & Foster, D. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072540 · Cited by 331

Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type

Boldog, E., Bakken, T. E., Hodge, R. D., Novotny, M., Aevermann, B. D., Baka, J., Bordé, S., Close, J. L., Diez-Fuertes, F., Ding, S.-L., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0205-2 · Cited by 291

The Intestine Harbors Functionally Distinct Homeostatic Tissue-Resident and Inflammatory Th17 Cells

Omenetti, S., Bussi, C., Metidji, A., Iseppon, A., Lee, S., Tolaini, M., Li, Y., Kelly, G., Chakravarty, P., Shoaie, S., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.05.004 · Cited by 317

Approach, avoidance, and affect: a meta-analysis of approach-avoidance tendencies in manual reaction time tasks

Phaf, R. H., Mohr, S. E., Rotteveel, M., & Wicherts, J. M. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00378 · Cited by 326

Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data

Holland, C. H., Tanevski, J., Perales-Patón, J., Gleixner, J., Kumar, M. P., Mereu, E., Joughin, B. A., Stegle, O., Lauffenburger, D. A., Heyn, H., et al. (2020) · Genome Biology · doi:10.1186/s13059-020-1949-z · Cited by 323

An investigation into per- and polyfluoroalkyl substances (PFAS) in nineteen Australian wastewater treatment plants (WWTPs)

Coggan, T. L., Moodie, D., Kolobaric, A., Szabo, D., Shimeta, J., Crosbie, N. D., Lee, E., Fernandes, M., & Clarke, B. O. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e02316 · Cited by 327

Conserved epigenetic sensitivity to early life experience in the rat and human hippocampus

Suderman, M., McGowan, P. O., Sasaki, A., Huang, T. C. T., Hallett, M. T., Meaney, M. J., Turecki, G., & Szyf, M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121260109 · Cited by 327

Risk factors for child sexual abuse victimization: A meta-analytic review.

Assink, M., van der Put, C. E., Meeuwsen, M. W. C. M., de Jong, N. M., Oort, F. J., Stams, G. J. J. M., & Hoeve, M. (2019) · Psychological bulletin · doi:10.1037/bul0000188 · Cited by 322

Impact of Dietary Resistant Starch on the Human Gut Microbiome, Metaproteome, and Metabolome

Maier, T. V., Lucio, M., Lee, L. H., VerBerkmoes, N. C., Brislawn, C. J., Bernhardt, J., Lamendella, R., McDermott, J. E., Bergeron, N., Heinzmann, S. S., et al. (2017) · mBio · doi:10.1128/mbio.01343-17 · Cited by 316

Pathology of Peripheral Artery Disease in Patients With Critical Limb Ischemia

Narula, N., Dannenberg, A. J., Olin, J. W., Bhatt, D. L., Johnson, K. W., Nadkarni, G., Min, J., Torii, S., Poojary, P., Anand, S. S., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.08.002 · Cited by 326

Internet-delivered cognitive behavior therapy for children and adolescents: A systematic review and meta-analysis

Vigerland, S., Lenhard, F., Bonnert, M., Lalouni, M., Hedman, E., Ahlen, J., Olén, O., Serlachius, E., & Ljótsson, B. (2016) · Clinical Psychology Review · doi:10.1016/j.cpr.2016.09.005 · Cited by 292

G1 Phase Regulation, Area-Specific Cell Cycle Control, and Cytoarchitectonics in the Primate Cortex

Lukaszewicz, A., Savatier, P., Cortay, V., Giroud, P., Huissoud, C., Berland, M., Kennedy, H., & Dehay, C. (2005) · Neuron · doi:10.1016/j.neuron.2005.06.032 · Cited by 315

Chronic stress-induced gut dysfunction exacerbates Parkinson's disease phenotype and pathology in a rotenone-induced mouse model of Parkinson's disease

Dodiya, H. B., Forsyth, C. B., Voigt, R. M., Engen, P. A., Patel, J., Shaikh, M., Green, S. J., Naqib, A., Roy, A., Kordower, J. H., et al. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2018.12.012 · Cited by 305

Mechanical properties of cortical bone and their relationships with age, gender, composition and microindentation properties in the elderly

Mirzaali, M. J., Schwiedrzik, J. J., Thaiwichai, S., Best, J. P., Michler, J., Zysset, P. K., & Wolfram, U. (2016) · Bone · doi:10.1016/j.bone.2015.11.018 · Cited by 325

Differential expression analysis for sequence count data

Anders, S., & Huber, W. (2010) · Nature Precedings · doi:10.1038/npre.2010.4282.1 · Cited by 328

Systematic reviews of categorical versus continuum models in psychosis: evidence for discontinuous subpopulations underlying a psychometric continuum. Implications for DSM-V, DSM-VI, and DSM-VII

Linscott, R. J., & van Os, J. (2010) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.032408.153506 · Cited by 324

Serious Games for Mental Health: Are They Accessible, Feasible, and Effective? A Systematic Review and Meta-analysis

Lau, H. M., Smit, J. H., Fleming, T. M., & Riper, H. (2017) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00209 · Cited by 328

Randomized controlled effectiveness trial of executive function intervention for children on the autism spectrum

Kenworthy, L., Anthony, L. G., Naiman, D. Q., Cannon, L., Wills, M. C., Luong‐Tran, C., Werner, M. A., Alexander, K. C., Strang, J., Bal, E., et al. (2014) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12161 · Cited by 323

Mindfulness-based interventions with youth: A comprehensive meta-analysis of group-design studies

Klingbeil, D. A., Renshaw, T. L., Willenbrink, J. B., Copek, R. A., Chan, K. T., Haddock, A., Yassine, J., & Clifton, J. (2017) · Journal of School Psychology · doi:10.1016/j.jsp.2017.03.006 · Cited by 312

Impaired Sensitivity to Thyroid Hormones Is Associated With Diabetes and Metabolic Syndrome

Laclaustra, M., Moreno-Franco, B., Lou-Bonafonte, J. M., Mateo-Gallego, R., Casasnovas, J. A., Guallar-Castillon, P., Cenarro, A., & Civeira, F. (2019) · Diabetes Care · doi:10.2337/dc18-1410 · Cited by 322

Prevalence of Depression After Spinal Cord Injury: A Meta-Analysis

Williams, R., & Murray, A. (2015) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2014.08.016 · Cited by 320

Tolerability of different oral iron supplements: a systematic review

Cancelo-Hidalgo, M. J., Castelo-Branco, C., Palacios, S., Haya-Palazuelos, J., Ciria-Recasens, M., Manasanch, J., & Pérez-Edo, L. (2013) · Current Medical Research and Opinion · doi:10.1185/03007995.2012.761599 · Cited by 320

Adult infiltrating gliomas with WHO 2016 integrated diagnosis: additional prognostic roles of ATRX and TERT

Pekmezci, M., Rice, T., Molinaro, A. M., Walsh, K. M., Decker, P. A., Hansen, H., Sicotte, H., Kollmeyer, T. M., McCoy, L. S., Sarkar, G., et al. (2017) · Acta Neuropathologica · doi:10.1007/s00401-017-1690-1 · Cited by 319

Guidelines for the use of acoustic indices in environmental research

Bradfer‐Lawrence, T., Gardner, N., Bunnefeld, L., Bunnefeld, N., Willis, S. G., & Dent, D. H. (2019) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13254 · Cited by 319

Defining a personal, allele-specific, and single-molecule long-read transcriptome

Tilgner, H., Grubert, F., Sharon, D., & Snyder, M. P. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400447111 · Cited by 266

Automated classification of bird and amphibian calls using machine learning: A comparison of methods

Acevedo, M. A., Corrada-Bravo, C. J., Corrada-Bravo, H., Villanueva-Rivera, L. J., & Aide, T. M. (2009) · Ecological Informatics · doi:10.1016/j.ecoinf.2009.06.005 · Cited by 317

Measuring depression over time … Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression

Fried, E. I., van Borkulo, C. D., Epskamp, S., Schoevers, R. A., Tuerlinckx, F., & Borsboom, D. (2016) · Psychological Assessment · doi:10.1037/pas0000275 · Cited by 314

Seasonal Variation in Human Gut Microbiome Composition

Davenport, E. R., Mizrahi-Man, O., Michelini, K., Barreiro, L. B., Ober, C., & Gilad, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0090731 · Cited by 314

Small studies are more heterogeneous than large ones: a meta-meta-analysis

IntHout, J., Ioannidis, J. P. A., Borm, G. F., & Goeman, J. J. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.03.017 · Cited by 314

Ungulate preference for burned patches reveals strength of fire–grazing interaction

Allred, B. W., Fuhlendorf, S. D., Engle, D. M., & Elmore, R. D. (2011) · Ecology and Evolution · doi:10.1002/ece3.12 · Cited by 313

When is hub gene selection better than standard meta-analysis?

Langfelder, P., Mischel, P. S., & Horvath, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061505 · Cited by 313

Long-term effects of lithium on renal, thyroid, and parathyroid function: a retrospective analysis of laboratory data

Shine, B., McKnight, R. F., Leaver, L., & Geddes, J. R. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61842-0 · Cited by 313

More diverse plant communities have higher functioning over time due to turnover in complementary dominant species

Allan, E., Weisser, W., Weigelt, A., Roscher, C., Fischer, M., & Hillebrand, H. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1104015108 · Cited by 312

Sewage Reflects the Microbiomes of Human Populations

Newton, R. J., McLellan, S. L., Dila, D. K., Vineis, J. H., Morrison, H. G., Eren, A. M., & Sogin, M. L. (2015) · mBio · doi:10.1128/mbio.02574-14 · Cited by 299

Empirical array quality weights in the analysis of microarray data

Ritchie, M. E., Diyagama, D., Neilson, J., van Laar, R., Dobrovic, A., Holloway, A., & Smyth, G. K. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-261 · Cited by 312

Longitudinal four-dimensional mapping of subcortical anatomy in human development

Raznahan, A., Shaw, P. W., Lerch, J. P., Clasen, L. S., Greenstein, D., Berman, R., Pipitone, J., Chakravarty, M. M., & Giedd, J. N. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316911111 · Cited by 312

EGFR–TKI-Associated Interstitial Pneumonitis in Nivolumab-Treated Patients With Non–Small Cell Lung Cancer

Oshima, Y., Tanimoto, T., Yuji, K., & Tojo, A. (2018) · JAMA Oncology · doi:10.1001/jamaoncol.2017.4526 · Cited by 313

Self-regulated learning partially mediates the effect of self-regulated learning interventions on achievement in higher education: A meta-analysis

Jansen, R. S., van Leeuwen, A., Janssen, J., Jak, S., & Kester, L. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.100292 · Cited by 310

Bayesian Random-Effects Meta-Analysis Using the bayesmeta R Package

Röver, C. (2020) · Journal of Statistical Software · doi:10.18637/jss.v093.i06 · Cited by 310

Effects of microplastic exposure on the body condition and behaviour of planktivorous reef fish (Acanthochromis polyacanthus)

Critchell, K., & Hoogenboom, M. O. (2018) · PLOS ONE · doi:10.1371/journal.pone.0193308 · Cited by 310

The impact of formative peer feedback on higher education students' academic writing: a Meta-Analysis

Huisman, B., Saab, N., van den Broek, P., & van Driel, J. (2019) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2018.1545896 · Cited by 306

Assessing the generalizability of randomized trial results to target populations

Stuart, E. A., Bradshaw, C. P., & Leaf, P. J. (2015) · Prevention Science · doi:10.1007/s11121-014-0513-z · Cited by 296

Resistant starch alters gut microbiome and metabolomic profiles concurrent with amelioration of chronic kidney disease in rats

Kieffer, D. A., Piccolo, B. D., Vaziri, N. D., Liu, S., Lau, W. L., Khazaeli, M., Nazertehrani, S., Moore, M. E., Marco, M. L., Martin, R. J., et al. (2016) · American Journal of Physiology-Renal Physiology · doi:10.1152/ajprenal.00513.2015 · Cited by 308

scds: computational annotation of doublets in single-cell RNA sequencing data

Bais, A. S., & Kostka, D. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz698 · Cited by 308

Environment characterization as an aid to wheat improvement: interpreting genotype–environment interactions by modelling water-deficit patterns in North-Eastern Australia

Chenu, K., Cooper, M., Hammer, G. L., Mathews, K. L., Dreccer, M. F., & Chapman, S. C. (2011) · Journal of Experimental Botany · doi:10.1093/jxb/erq459 · Cited by 298

Comparison of reading performance on screen and on paper: A meta-analysis

Kong, Y., Seo, Y. S., & Zhai, L. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.05.005 · Cited by 306

The cancer stem cell marker aldehyde dehydrogenase is required to maintain a drug-tolerant tumor cell subpopulation

Raha, D., Wilson, T. R., Peng, J., Peterson, D., Yue, P., Evangelista, M., Wilson, C., Merchant, M., & Settleman, J. (2014) · Cancer Research · doi:10.1158/0008-5472.can-13-3456 · Cited by 307

Somatic mosaicism and allele complexity induced by CRISPR/Cas9 RNA injections in mouse zygotes

Yen, S.-T., Zhang, M., Deng, J. M., Usman, S. J., Smith, C. N., Parker-Thornburg, J., Swinton, P. G., Martin, J. F., & Behringer, R. R. (2014) · Developmental Biology · doi:10.1016/j.ydbio.2014.06.017 · Cited by 300

Ocean Acidification-Induced Food Quality Deterioration Constrains Trophic Transfer

Rossoll, D., Bermúdez, R., Hauss, H., Schulz, K. G., Riebesell, U., Sommer, U., & Winder, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034737 · Cited by 293

Dynamics of the skeletal muscle secretome during myoblast differentiation

Henningsen, J., Rigbolt, K. T. G., Blagoev, B., Pedersen, B. K., & Kratchmarova, I. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m110.002113 · Cited by 303

Toward a comprehensive and potentially cross-cultural model of why people engage in collective action: a quantitative research synthesis of four motivations and structural constraints

Agostini, M., & van Zomeren, M. (2021) · Psychological Bulletin · doi:10.1037/bul0000256 · Cited by 301

Mapping human pressures on biodiversity across the planet uncovers anthropogenic threat complexes

Bowler, D. E., Bjorkman, A. D., Dornelas, M., Myers‐Smith, I. H., Navarro, L. M., Niamir, A., Supp, S. R., Waldock, C., Winter, M., Vellend, M., et al. (2020) · People and Nature · doi:10.1002/pan3.10071 · Cited by 287

Improving inferences about null effects with Bayes factors and equivalence tests.

Lakens, D., McLatchie, N., Isager, P. M., Scheel, A. M., & Dienes, Z. (2020) · The Journals of Gerontology: Series B · doi:10.1093/geronb/gby065 · Cited by 279

Unraveling the comorbidity of depression and anxiety in a large inpatient sample: Network analysis to examine bridge symptoms

Kaiser, T., Herzog, P., Voderholzer, U., & Brakemeier, E. (2021) · Depression and Anxiety · doi:10.1002/da.23136 · Cited by 296

Ancient west Eurasian ancestry in southern and eastern Africa

Pickrell, J. K., Patterson, N., Loh, P.-R., Lipson, M., Berger, B., Stoneking, M., Pakendorf, B., & Reich, D. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313787111 · Cited by 300

SURFACE : detecting convergent evolution from comparative data by fitting Ornstein‐Uhlenbeck models with stepwise Akaike Information Criterion

Ingram, T., & Mahler, D. L. (2013) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12034 · Cited by 300

Neoadjuvant plus adjuvant dabrafenib and trametinib versus standard of care in patients with high-risk, surgically resectable melanoma: a single-centre, open-label, randomised, phase 2 trial

Amaria, R. N., Prieto, P. A., Tetzlaff, M. T., Reuben, A., Andrews, M. C., Ross, M. I., Glitza, I. C., Cormier, J., Hwu, W.-J., Tawbi, H. A., et al. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30015-9 · Cited by 299

Unseen wounds: The contribution of psychological maltreatment to child and adolescent mental health and risk outcomes.

Spinazzola, J., Hodgdon, H., Liang, L.-J., Ford, J. D., Layne, C. M., Pynoos, R., Briggs, E. C., Stolbach, B., & Kisiel, C. (2014) · Psychological Trauma: Theory, Research, Practice, and Policy · doi:10.1037/a0037766 · Cited by 297

Social Structure, Infectious Diseases, Disasters, Secularism, and Cultural Change in America

Grossmann, I., & Varnum, M. E. W. (2015) · Psychological Science · doi:10.1177/0956797614563765 · Cited by 299

Obesity and iron deficiency: A quantitative meta-analysis

Zhao, L., Zhang, X., Shen, Y., Fang, X., Wang, Y., & Wang, F. (2015) · Obesity Reviews · doi:10.1111/obr.12323 · Cited by 286

Hierarchical Control of Dopamine Neuron-Firing Patterns by Nicotinic Receptors

Mameli-Engvall, M., Evrard, A., Pons, S., Maskos, U., Svensson, T. H., Changeux, J.-P., & Faure, P. (2006) · Neuron · doi:10.1016/j.neuron.2006.05.007 · Cited by 296

Gastrointestinal symptoms in autism spectrum disorder: A review of the literature on ascertainment and prevalence

Holingue, C., Newill, C., Lee, L., Pasricha, P. J., & Daniele Fallin, M. (2018) · Autism Research · doi:10.1002/aur.1854 · Cited by 296

To test or not to test: Preliminary assessment of normality when comparing two independent samples

Rochon, J., Gondan, M., & Kieser, M. (2012) · BMC Medical Research Methodology · doi:10.1186/1471-2288-12-81 · Cited by 296

Post-fire vegetation and fuel development influences fire severity patterns in reburns

Coppoletta, M., Merriam, K. E., & Collins, B. M. (2016) · Ecological Applications · doi:10.1890/15-0225 · Cited by 295

Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning

Stowell, D., & Plumbley, M. D. (2014) · PeerJ · doi:10.7717/peerj.488 · Cited by 295

Explainable artificial intelligence for breast cancer: A visual case-based reasoning approach

Lamy, J.-B., Sekar, B., Guezennec, G., Bouaud, J., & Séroussi, B. (2019) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2019.01.001 · Cited by 282

How diverse is child language acquisition research?

Kidd, E., & Garcia, R. (2022) · First Language · doi:10.1177/01427237211066405 · Cited by 283

Propensity-Matched Comparisons of Clinical Outcomes After Transapical or Transfemoral Transcatheter Aortic Valve Replacement: A Placement of Aortic Transcatheter Valves (PARTNER)-I Trial Substudy

Blackstone, E. H., Suri, R. M., Rajeswaran, J., Babaliaros, V., Douglas, P. S., Fearon, W. F., Miller, D. C., Hahn, R. T., Kapadia, S., Kirtane, A. J., et al. (2015) · Circulation · doi:10.1161/circulationaha.114.012525 · Cited by 290

Interferon-γ links ultraviolet radiation to melanomagenesis in mice

Zaidi, M. R., Davis, S., Noonan, F. P., Graff-Cherry, C., Hawley, T. S., Walker, R. L., Feigenbaum, L., Fuchs, E., Lyakh, L., Young, H. A., et al. (2011) · Nature · doi:10.1038/nature09666 · Cited by 293

Remedies for pseudoreplication

Millar, R. B., & Anderson, M. J. (2004) · Fisheries Research · doi:10.1016/j.fishres.2004.08.016 · Cited by 292

Biochar amendment to soil changes dissolved organic matter content and composition

Smebye, A., Alling, V., Vogt, R. D., Gadmar, T. C., Mulder, J., Cornelissen, G., & Hale, S. E. (2016) · Chemosphere · doi:10.1016/j.chemosphere.2015.04.087 · Cited by 292

The effectiveness of hypnosis for pain relief: a systematic review and meta-analysis of 85 controlled experimental trials

Thompson, T., Terhune, D. B., Oram, C., Sharangparni, J., Rouf, R., Solmi, M., Veronese, N., & Stubbs, B. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.02.013 · Cited by 285

Marine anoxia and delayed Earth system recovery after the end-Permian extinction

Lau, K. V., Maher, K., Altiner, D., Kelley, B. M., Kump, L. R., Lehrmann, D. J., Silva-Tamayo, J. C., Weaver, K. L., Yu, M., & Payne, J. L. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1515080113 · Cited by 294

Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load

Wielgoss, S., Barrick, J. E., Tenaillon, O., Wiser, M. J., Dittmar, W. J., Cruveiller, S., Chane-Woon-Ming, B., Médigue, C., Lenski, R. E., & Schneider, D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219574110 · Cited by 292

The National Fire and Fire Surrogate study: Effects of fuel reduction methods on forest vegetation structure and fuels

Schwilk, D. W., Keeley, J. E., Knapp, E. E., McIver, J., Bailey, J. D., Fettig, C. J., Fiedler, C. E., Harrod, R. J., Moghaddas, J. J., Outcalt, K. W., et al. (2009) · Ecological Applications · doi:10.1890/07-1747.1 · Cited by 291

How self‐generated thought shapes mood–the relation between mind‐wandering and mood depends on the socio‐temporal content of thoughts

Ruby, F. J. M., Smallwood, J., Engen, H., & Singer, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077554 · Cited by 275

Microplastics in the Arctic: A Case Study with Sub-Surface Water and Fish Samples off Northeast Greenland

Morgana, S., Ghigliotti, L., Estévez-Calvar, N., Stifanese, R., Wieckzorek, A., Doyle, T., Christiansen, J. S., Faimali, M., & Garaventa, F. (2018) · Environmental Pollution · doi:10.1016/j.envpol.2018.08.001 · Cited by 289

Several scales of biodiversity affect ecosystem multifunctionality

Pasari, J. R., Levi, T., Zavaleta, E. S., & Tilman, D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1220333110 · Cited by 289

Microplastics alter composition of fungal communities in aquatic ecosystems

Kettner, M. T., Rojas‐Jimenez, K., Oberbeckmann, S., Labrenz, M., & Grossart, H. (2017) · Environmental Microbiology · doi:10.1111/1462-2920.13891 · Cited by 282

Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships

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Construction of the Average Variance Extracted Index for Construct Validation in Structural Equation Models with Adaptive Regressions

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Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands.

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