You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 thrombosis_prediction
【Schema】
# Table: Laboratory
[
(ID:INTEGER, Primary Key, Examples: [27654, 30609, 43003]),
(Date:DATE, Primary Key, Examples: [1991-09-11]),
(GOT:INTEGER, Examples: [34, 29, 26]),
(GPT:INTEGER, Examples: [36, 31, 22]),
(LDH:INTEGER, Examples: [567, 579, 684]),
(ALP:INTEGER, Examples: [166, 154, 138]),
(TP:REAL, Examples: [4.5, 5.1, 5.5]),
(ALB:REAL, Examples: [3.3, 3.4, 3.6]),
(UA:REAL, Examples: [3.8, 4.2, 4.9]),
(UN:INTEGER, Examples: [29, 36, 34]),
(CRE:REAL, Examples: [0.8, 0.9, 0.7]),
(T-BIL:REAL, Examples: [0.3, 0.2, 0.4]),
(T-CHO:INTEGER, Examples: [165, 134, 140]),
(TG:INTEGER, Examples: [185, 205, 254]),
(CPK:INTEGER, Examples: [9, 10, 11]),
(GLU:INTEGER, Examples: [88, 134, 161]),
(WBC:REAL, Examples: [5.0, 10.4, 10.5]),
(RBC:REAL, Examples: [2.6, 2.9, 3.4]),
(HGB:REAL, Examples: [6.4, 6.7, 7.9]),
(HCT:REAL, Examples: [20.3, 21.6, 24.7]),
(PLT:INTEGER, Examples: [227, 242, 233]),
(PT:REAL, Examples: [11.3, 12.0, 11.8]),
(APTT:INTEGER, Examples: [108, 84, 76]),
(FG:REAL, Examples: [27.0, 38.6, 27.6]),
(PIC:INTEGER, Examples: [320, 513, 284]),
(TAT:INTEGER, Examples: [77, 108, 115]),
(TAT2:INTEGER, Examples: [113, 88, 104]),
(U-PRO:TEXT, Examples: [-, 0, TR]),
(IGG:INTEGER, Examples: [339, 771, 430]),
(IGA:INTEGER, Examples: [145, 188, 118]),
(IGM:INTEGER, Examples: [46, 132, 56]),
(CRP:TEXT, Examples: [0.6, 2.7, 1.2]),
(RA:TEXT, Examples: [-, +, +-]),
(RF:TEXT, Examples: [<20.5, <20.8, <40]),
(C3:INTEGER, Examples: [30, 82, 103]),
(C4:INTEGER, Examples: [14, 26, 35]),
(RNP:TEXT, Examples: [0, 1, 256]),
(SM:TEXT, Examples: [0, 1, negative]),
(SC170:TEXT, Examples: [16, 1, 0]),
(SSA:TEXT, Examples: [0, negative, 16]),
(SSB:TEXT, Examples: [0, negative, 1]),
(CENTROMEA:TEXT, Examples: [0, negative]),
(DNA:TEXT, Examples: [41.9, 18, 4.3]),
(DNA-II:INTEGER)
]
# Table: Patient
[
(ID:INTEGER, Primary Key, Examples: [2110, 11408, 12052]),
(SEX:TEXT, Examples: [F, M]),
(Birthday:DATE, Examples: [1934-02-13]),
(Description:DATE, Examples: [1994-02-14]),
(First Date:DATE, Examples: [1993-02-10]),
(Admission:TEXT, Examples: [+, -, +(]),
(Diagnosis:TEXT, Examples: [RA susp., PSS, SLE])
]
# Table: Examination
[
(ID:INTEGER, Examples: [14872, 48473, 102490]),
(Examination Date:DATE, Examples: [1997-05-27]),
(aCL IgG:REAL, Examples: [1.3, 4.3, 2.3]),
(aCL IgM:REAL, Examples: [1.6, 4.6, 2.5]),
(ANA:INTEGER, Examples: [256, 0, 16]),
(ANA Pattern:TEXT, Examples: [P, P,S, S]),
(aCL IgA:INTEGER, Examples: [0, 3, 4]),
(Diagnosis:TEXT, Examples: [MCTD, AMI, SLE, PSS]),
(KCT:TEXT, Examples: [-, +]),
(RVVT:TEXT, Examples: [-, +]),
(LAC:TEXT, Examples: [-, +]),
(Symptoms:TEXT, Examples: [AMI, CNS lupus, Apo]),
(Thrombosis:INTEGER, Examples: [1, 0, 2])
]
【Foreign keys】
Laboratory.ID=Patient.ID
Examination.ID=Patient.ID

    【Question】
    List the patient ID, sex and birthday who has abnormal white blood cell count. Group them by sex and list the patient by age in ascending order. abnormal white blood cell count refers to WBC < = 3.5 or WBC > = 9.0;

    【Evidence】
    abnormal white blood cell count refers to WBC < = 3.5 or WBC > = 9.0;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT DISTINCT T1.ID, T1.SEX, T1.Birthday FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.WBC <= 3.5 OR T2.WBC >= 9.0 GROUP BY T1.SEX,T1.ID ORDER BY T1.Birthday ASC