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 ID, sex and date of birth of patient whose total protein (TP) below the lower range of the normal index. total protein (TP) below the lower range of the normal index refers to TP < 6.0

    【Evidence】
    total protein (TP) below the lower range of the normal index refers to TP < 6.0

    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.TP < 6.0