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1Statistics in brief: Statistical power: what is it and when should it be used?
F. Dorey. Clinical orthopaedics and related research, 469 (2): 619-20 (February 2011)6031<m:linebreak></m:linebreak>JID: 0075674; ppublish;<m:linebreak></m:linebreak>Sample size; Power.
2 years ago by @jepcastel
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MathematicalComputing
SampleSize
Humans
Statistical
Models
ProbabilityTheory
ClinicalTrialsasTopic
DataInterpretation
MathematicalComputingSampleSizeHumansStatisticalModelsProbabilityTheoryClinicalTrialsasTopicDataInterpretation
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1Measures of effect based on the sufficient causes model. 1. Risks and rates of disease associated with a single causative agent.
R. Allard, and J. Boivin. Epidemiology (Cambridge, Mass.), 4 (1): 37-42 (January 1993)2557<m:linebreak></m:linebreak>Comment in: Epidemiology 1993 Jul;4(4):385; discussion 386-7; Comment in: Epidemiology 1993 Jul;4(4):386; discussion 386-7;<m:linebreak></m:linebreak>Mesures d'associació.
2 years ago by @jepcastel
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Zidovudine:adverseeffects
AcquiredImmunodeficiencySyndrome:drugtherapy
EpidemiologicMethods
Case-ControlStudies
Humans
Zidovudine:therapeuticuse
Risk
Statistical
Models
AcquiredImmunodeficiencySyndrome
Zidovudine
Causality
Zidovudine:adverseeffectsAcquiredImmunodeficiencySyndrome:drugtherapyEpidemiologicMethodsCase-ControlStudiesHumansZidovudine:therapeuticuseRiskStatisticalModelsAcquiredImmunodeficiencySyndromeZidovudineCausality
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1Measures of effect based on the sufficient causes model. 2. Risks and rates of disease associated with a single preventive agent.
R. Allard, and J. Boivin. Epidemiology (Cambridge, Mass.), 4 (6): 517-23 (November 1993)3147<m:linebreak></m:linebreak>Mesures d'associació.
2 years ago by @jepcastel
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AIDS-RelatedComplex:prevention&control
Humans
Zidovudine:therapeuticuse
Probability
AcquiredImmunodeficiencySyndrome
AIDS-RelatedOpportunisticInfections
Biometry
AIDS-RelatedComplex
AcquiredImmunodeficiencySyndrome:epidemiology
EpidemiologicMethods
RiskFactors
Case-ControlStudies
AIDS-RelatedComplex:epidemiology
Statistical
Models
ConfoundingFactors(Epidemiology)
AcquiredImmunodeficiencySyndrome:prevention&c
Zidovudine
AIDS-RelatedOpportunisticInfections:epidemiolog
AIDS-RelatedComplex:prevention&controlHumansZidovudine:therapeuticuseProbabilityAcquiredImmunodeficiencySyndromeAIDS-RelatedOpportunisticInfectionsBiometryAIDS-RelatedComplexAcquiredImmunodeficiencySyndrome:epidemiologyEpidemiologicMethodsRiskFactorsCase-ControlStudiesAIDS-RelatedComplex:epidemiologyStatisticalModelsConfoundingFactors(Epidemiology)AcquiredImmunodeficiencySyndrome:prevention&cZidovudineAIDS-RelatedOpportunisticInfections:epidemiolog
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1How and why to prepare a protocol.
J. Antònio. Medicina clínica, 106 (7): 257-62 (February 1996)4355<m:linebreak></m:linebreak>LR: 20071115; PUBM: Print; JID: 0376377; ppublish;<m:linebreak></m:linebreak>Protocol.
2 years ago by @jepcastel
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ClinicalProtocols
Theoretical
Animals
ResearchSupportasTopic
ResearchDesign
Humans
Statistical
Models
PilotProjects
Medical
DataInterpretation
Ethics
ClinicalProtocolsTheoreticalAnimalsResearchSupportasTopicResearchDesignHumansStatisticalModelsPilotProjectsMedicalDataInterpretationEthics
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1Estimating sample size for epidemiologic studies: the impact of ignoring exposure measurement uncertainty.
O. Devine, and J. Smith. Statistics in medicine, 17 (12): 1375-89 (June 1998)2463.
2 years ago by @jepcastel
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LikelihoodFunctions
EpidemiologicStudies
Humans
IodineRadioisotopes
Neoplasms
Radiation-Induced
AgeFactors
ThyroidNeoplasms:etiology
Radiation-Induced:etiology
SelectionBias
ThyroidNeoplasms:epidemiology
SampleSize
RiskFactors
Adolescent
Radiation-Induced:epidemiology
IodineRadioisotopes:adverseeffects
Statistical
Models
ThyroidNeoplasms
Child
CohortStudies
RadiationDosage
LikelihoodFunctionsEpidemiologicStudiesHumansIodineRadioisotopesNeoplasmsRadiation-InducedAgeFactorsThyroidNeoplasms:etiologyRadiation-Induced:etiologySelectionBiasThyroidNeoplasms:epidemiologySampleSizeRiskFactorsAdolescentRadiation-Induced:epidemiologyIodineRadioisotopes:adverseeffectsStatisticalModelsThyroidNeoplasmsChildCohortStudiesRadiationDosage
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1Causal directed acyclic graphs and the direction of unmeasured confounding bias.
T. VanderWeele, M. Hernán, and J. Robins. Epidemiology (Cambridge, Mass.), 19 (5): 720-8 (September 2008)5052<m:linebreak></m:linebreak>JID: 9009644; ppublish;<m:linebreak></m:linebreak>Mesures d'associació.
2 years ago by @jepcastel
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Humans
Statistical
Models
ConfoundingFactors(Epidemiology)
Bias(Epidemiology)
Causality
HumansStatisticalModelsConfoundingFactors(Epidemiology)Bias(Epidemiology)Causality
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1A comparison between traditional methods and multilevel regression for the analysis of multicenter intervention studies.
M. Moerbeek, G. van Breukelen, and M. Berger. Journal of clinical epidemiology, 56 (4): 341-50 (April 2003)3107<m:linebreak></m:linebreak>Multilevel.
2 years ago by @jepcastel
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RCT
ResearchDesign
Humans
Smoking:prevention&control
DataInterpretation
MulticenterStudiesasTopic:methods
Adolescent
Smoking
Statistical
Models
RegressionAnalysis
Child
MulticenterStudiesasTopic
TreatmentOutcome
ClusterAnalysis
RCTResearchDesignHumansSmoking:prevention&controlDataInterpretationMulticenterStudiesasTopic:methodsAdolescentSmokingStatisticalModelsRegressionAnalysisChildMulticenterStudiesasTopicTreatmentOutcomeClusterAnalysis
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1The problem of therapeutic efficacy indices. 1. Elements of the problem.
J. Boissel, M. Cucherat, F. Gueyffier, G. Chatellier, M. Buyse, W. Li, F. Boutitie, P. Nony, M. Haugh, and G. Mignot. Thérapie, 54 (2): 203-7 (1999)2966<m:linebreak></m:linebreak>Mesures de contrast.
2 years ago by @jepcastel
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Meta-AnalysisasTopic
RiskAssessment
Theoretical
Humans
Models
ClinicalTrialsasTopic
TreatmentOutcome
Meta-AnalysisasTopicRiskAssessmentTheoreticalHumansModelsClinicalTrialsasTopicTreatmentOutcome
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1Formal approaches to safety monitoring of clinical trials in life-threatening conditions.
K. Bolland, and J. Whitehead. Statistics in medicine, 19 (21): 2899-917 (November 2000)3639<m:linebreak></m:linebreak>Mesures d'associació.
2 years ago by @jepcastel
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CraniocerebralTrauma
ClinicalTrials
Humans
MyocardialInfarction:mortality
Probability
MyocardialInfarction
ClinicalTrialsasTopic:statistics&numericald
Stroke:mortality
DataInterpretation
Stroke
CraniocerebralTrauma:drugtherapy
MyocardialInfarction:drugtherapy
NormalDistribution
Safety:statistics&numericaldata
CraniocerebralTrauma:mortality
Safety
Statistical
Models
MulticenterStudiesasTopic:statistics&numeric
MulticenterStudiesasTopic
ClinicalTrialsasTopic
Stroke:drugtherapy
PhaseIIIasTopic:statistics&numericaldata
PhaseIIIasTopic
CraniocerebralTraumaClinicalTrialsHumansMyocardialInfarction:mortalityProbabilityMyocardialInfarctionClinicalTrialsasTopic:statistics&numericaldStroke:mortalityDataInterpretationStrokeCraniocerebralTrauma:drugtherapyMyocardialInfarction:drugtherapyNormalDistributionSafety:statistics&numericaldataCraniocerebralTrauma:mortalitySafetyStatisticalModelsMulticenterStudiesasTopic:statistics&numericMulticenterStudiesasTopicClinicalTrialsasTopicStroke:drugtherapyPhaseIIIasTopic:statistics&numericaldataPhaseIIIasTopic
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1Working covariance model selection for generalized estimating equations.
V. Carey, and Y. Wang. Statistics in medicine, 30 (26): 3117-24 (November 2011)6264.
2 years ago by @jepcastel
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gamma-AminobutyricAcid:therapeuticuse
RCT
Software:statistics&numericaldata
Humans
RandomizedControlledTrialsasTopic:statistics
gamma-AminobutyricAcid:analogs&derivatives
Epilepsy
LongitudinalStudies
DataInterpretation
ComputerSimulation
Anticonvulsants
LongitudinalStudies:statistics&numericaldata
NormalDistribution
gamma-AminobutyricAcid
Anticonvulsants:therapeuticuse
Statistical
Models
Software
Epilepsy:epidemiology
gamma-AminobutyricAcid:therapeuticuseRCTSoftware:statistics&numericaldataHumansRandomizedControlledTrialsasTopic:statisticsgamma-AminobutyricAcid:analogs&derivativesEpilepsyLongitudinalStudiesDataInterpretationComputerSimulationAnticonvulsantsLongitudinalStudies:statistics&numericaldataNormalDistributiongamma-AminobutyricAcidAnticonvulsants:therapeuticuseStatisticalModelsSoftwareEpilepsy:epidemiology
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1Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders.
T. Vanderweele, and O. Arah. Epidemiology (Cambridge, Mass.), 22 (1): 42-52 (January 2011)6262<m:linebreak></m:linebreak>LR: 20110412; GR: R03 HD060696-01A1/HD/NICHD NIH HHS/United States; JID: 9009644; NIHMS239676; OID: NLM: NIHMS239676 Available on 01/01/12; OID: NLM: PMC3073860 Available on 01/01/12; PMCR: 2012/01/01; ppublish;.
2 years ago by @jepcastel
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EpidemiologicStudies
Humans
Statistical
Models
ConfoundingFactors(Epidemiology)
Bias(Epidemiology)
SensitivityandSpecificity
EpidemiologicStudiesHumansStatisticalModelsConfoundingFactors(Epidemiology)Bias(Epidemiology)SensitivityandSpecificity
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1Designing and analyzing clinical trials with composite outcomes: consideration of possible treatment differences between the individual outcomes.
J. Pogue, P. Devereaux, L. Thabane, and S. Yusuf. PloS one, 7 (4): e34785 (January 2012)6637<m:linebreak></m:linebreak>JID: 101285081; OID: NLM: PMC3328496; 2011/11/08 received; 2012/03/09 accepted; 2012/04/17 epublish; ppublish;<m:linebreak></m:linebreak>Comparacions múltiples; Composite endpoints; RCT; Heterogeneïtat.
2 years ago by @jepcastel
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BiomedicalResearch
RCT
ResearchDesign
Humans
Statistical
Models
TreatmentOutcome
BiomedicalResearchRCTResearchDesignHumansStatisticalModelsTreatmentOutcome
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1Treatment effects in the presence of unmeasured confounding: dealing with observations in the tails of the propensity score distribution--a simulation study.
T. Stürmer, K. Rothman, J. Avorn, and R. Glynn. American journal of epidemiology, 172 (7): 843-54 (October 2010)5732<m:linebreak></m:linebreak>JID: 7910653; aheadofprint;<m:linebreak></m:linebreak>Propensity score.
2 years ago by @jepcastel
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ResearchDesign
Humans
Calibration
SurvivalRate
ComputerSimulation
EpidemiologicMethods
ResearchDesign:statistics&numericaldata
Statistical
Models
ConfoundingFactors(Epidemiology)
Bias(Epidemiology)
RegressionAnalysis
CohortStudies
ResearchDesignHumansCalibrationSurvivalRateComputerSimulationEpidemiologicMethodsResearchDesign:statistics&numericaldataStatisticalModelsConfoundingFactors(Epidemiology)Bias(Epidemiology)RegressionAnalysisCohortStudies
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1Interpreting parameters in the logistic regression model with random effects.
K. Larsen, J. Petersen, E. Budtz-Jørgensen, and L. Endahl. Biometrics, 56 (3): 909-14 (September 2000)3544<m:linebreak></m:linebreak>Regressió logística.
2 years ago by @jepcastel
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Urodela
Male
Biological
SexualBehavior
RandomAllocation
Animal
Animals
Reproduction
OddsRatio
Statistical
Models
RegressionAnalysis
Female
UrodelaMaleBiologicalSexualBehaviorRandomAllocationAnimalAnimalsReproductionOddsRatioStatisticalModelsRegressionAnalysisFemale
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1Prognostic markers: data misinterpretation often leads to overoptimistic conclusions.
Y. Foucher, C. Combescure, J. Ashton-Chess, and M. Giral. American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons, 12 (4): 1060-1 (April 2012)6790<br/>JID: 100968638; CON: Am J Transplant. 2010 Sep;10(9):2066-73. PMID: 20883541; CON: Am J Transplant. 2008 Jun;8(6):1205-13. PMID: 18444921; CON: Am J Transplant. 2008 Dec;8(12):2537-46. PMID: 18945283; 2012/01/06 aheadofprint; ppublish;<br/>Models predictius; Proves diagnòstiques.
2 years ago by @jepcastel
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EndocrineGlandNeoplasms
KidneyTransplantation:pathology
EndocrineGlandNeoplasms:surgery
Humans
Male
KidneyTransplantation
KidneyTubules
OutcomeAssessment(HealthCare):methods
OutcomeAssessment(HealthCare)
Nephritis:pathology
LiverNeoplasms
Nephritis
DecisionSupportTechniques
EndpointDetermination:methods
Theoretical
LiverNeoplasms:surgery
LiverTransplantation
NeuroendocrineTumors
LiverTransplantation:mortality
Models
KidneyTubules:pathology
NeuroendocrineTumors:surgery
EndpointDetermination
Female
EndocrineGlandNeoplasmsKidneyTransplantation:pathologyEndocrineGlandNeoplasms:surgeryHumansMaleKidneyTransplantationKidneyTubulesOutcomeAssessment(HealthCare):methodsOutcomeAssessment(HealthCare)Nephritis:pathologyLiverNeoplasmsNephritisDecisionSupportTechniquesEndpointDetermination:methodsTheoreticalLiverNeoplasms:surgeryLiverTransplantationNeuroendocrineTumorsLiverTransplantation:mortalityModelsKidneyTubules:pathologyNeuroendocrineTumors:surgeryEndpointDeterminationFemale
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1Propensity score methods for confounding control in nonexperimental research.
M. Brookhart, R. Wyss, J. Layton, and T. Stürmer. Circulation. Cardiovascular quality and outcomes, 6 (5): 604-11 (September 2013)Propensity score; Introductori; CV; SAS.
2 years ago by @jepcastel
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Angioedema:chemicallyinduced
DataMining:statistics&numericaldata
Angioedema
Humans
PropensityScore
DataInterpretation
DataMining
AngiotensinIIType1ReceptorBlockers
ReproducibilityofResults
AngiotensinIIType1ReceptorBlockers:adversee
RiskFactors
Angiotensin-ConvertingEnzymeInhibitors:adverse
Statistical
Models
ConfoundingFactors(Epidemiology)
Angiotensin-ConvertingEnzymeInhibitors
Angioedema:chemicallyinducedDataMining:statistics&numericaldataAngioedemaHumansPropensityScoreDataInterpretationDataMiningAngiotensinIIType1ReceptorBlockersReproducibilityofResultsAngiotensinIIType1ReceptorBlockers:adverseeRiskFactorsAngiotensin-ConvertingEnzymeInhibitors:adverseStatisticalModelsConfoundingFactors(Epidemiology)Angiotensin-ConvertingEnzymeInhibitors
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1Classification to ordinal categories using a search partition methodology with an application in diabetes screening.
R. Marshall. Statistics in medicine, 18 (20): 2723-35 (October 1999)3326<m:linebreak></m:linebreak>Classification trees.
2 years ago by @jepcastel
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Fructosamine
Albuminuria:urine
MassScreening:methods
Humans
Triglycerides:blood
DiabetesMellitus:diagnosis
Male
Glucose
LogisticModels
Albuminuria
AgeFactors
Cholesterol
Glucose:metabolism
DecisionTrees
Triglycerides
Arteriosclerosis:classification
Arteriosclerosis
MassScreening
Statistical
Models
ContinentalPopulationGroups
Fructosamine:blood
DiabetesMellitus
Cholesterol:blood
FructosamineAlbuminuria:urineMassScreening:methodsHumansTriglycerides:bloodDiabetesMellitus:diagnosisMaleGlucoseLogisticModelsAlbuminuriaAgeFactorsCholesterolGlucose:metabolismDecisionTreesTriglyceridesArteriosclerosis:classificationArteriosclerosisMassScreeningStatisticalModelsContinentalPopulationGroupsFructosamine:bloodDiabetesMellitusCholesterol:blood
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1Health metrics and evaluation: strengthening the science.
C. Murray, and J. Frenk. Lancet, 371 (9619): 1191-9 (April 2008)4583<m:linebreak></m:linebreak>PUBM: Print; JID: 2985213R; CIN: Lancet. 2008 Apr 5;371(9619):1139-40. PMID: 18395559; RF: 90; ppublish;<m:linebreak></m:linebreak>Mesures de resultats.
2 years ago by @jepcastel
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ValidationStudiesasTopic
CommunityHealthPlanning:organization&administ
Biological
CommunityHealthPlanning:trends
HealthStatus
VitalStatistics
Forecasting
ResourceAllocation:organization&administration
Animals
CommunityHealthServices:trends
Cost-BenefitAnalysis
ProgramEvaluation:methods
Models
InformationSystems
CommunityHealthPlanning
WorldHealth
RiskAssessment
Humans
CommunityHealthServices
ResourceAllocation
CommunityHealthServices:organization&administ
InformationSystems:organization&administration
ProgramEvaluation
PolicyMaking
ResourceAllocation:methods
CommunicationBarriers
CommunityHealthPlanning:methods
ValidationStudiesasTopicCommunityHealthPlanning:organization&administBiologicalCommunityHealthPlanning:trendsHealthStatusVitalStatisticsForecastingResourceAllocation:organization&administrationAnimalsCommunityHealthServices:trendsCost-BenefitAnalysisProgramEvaluation:methodsModelsInformationSystemsCommunityHealthPlanningWorldHealthRiskAssessmentHumansCommunityHealthServicesResourceAllocationCommunityHealthServices:organization&administInformationSystems:organization&administrationProgramEvaluationPolicyMakingResourceAllocation:methodsCommunicationBarriersCommunityHealthPlanning:methods
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1The number of patients and events required to limit the risk of overestimation of intervention effects in meta-analysis--a simulation study.
K. Thorlund, G. Imberger, M. Walsh, R. Chu, C. Gluud, J. Wetterslev, G. Guyatt, P. Devereaux, and L. Thabane. PloS one, 6 (10): e25491 (January 2011)6400<m:linebreak></m:linebreak>JID: 101285081; 2011/02/24 received; 2011/09/06 accepted; 2011/10/18 epublish; ppublish;.
2 years ago by @jepcastel
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Meta-AnalysisasTopic
Theoretical
SampleSize
ResearchDesign
Humans
Risk
Probability
Models
Meta-AnalysisasTopicTheoreticalSampleSizeResearchDesignHumansRiskProbabilityModels
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1The efficiency of simulation-based multiple comparisons.
D. Edwards, and J. Berry. Biometrics, 43 (4): 913-28 (December 1987)7102<m:linebreak></m:linebreak>LR: 20071114; GR: GM36977-01/GM/NIGMS NIH HHS/United States; GR: R01 GM34870-01/GM/NIGMS NIH HHS/United States; GR: R01 HL24314/HL/NHLBI NIH HHS/United States; GR: etc.; JID: 0370625; ppublish;<m:linebreak></m:linebreak>Comparacions múltiples.
2 years ago by @jepcastel
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AnalysisofVariance
Cats
ResearchDesign
CapillaryPermeability
Probability
Mathematics
Biological
ComputerSimulation
Animals
PredatoryBehavior
Fishes
Decapoda(Crustacea)
Models
AnalysisofVarianceCatsResearchDesignCapillaryPermeabilityProbabilityMathematicsBiologicalComputerSimulationAnimalsPredatoryBehaviorFishesDecapoda(Crustacea)Models
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publications (hide)257
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