file,variable,type,unit,allowed_values,description,missing_values,provenance,derivation,example
patient_bg.csv,patient_id,string,,,Optional unique patient identifier if added.,,01_stroke_synth.py,generated/sequenced,P000123
patient_bg.csv,sex,category,,"M,F",Biological sex.,,01_stroke_synth.py,sampling,M
patient_bg.csv,age,integer,years,18–99,Age at admission.,,01_stroke_synth.py,sampling,78
patient_bg.csv,nihss,integer,score,0–42,NIH Stroke Scale at arrival.,,01_stroke_synth.py,threshold-fit + discrete sampling,6
patient_bg.csv,pre_mrs,integer,score,0–5,Pre-stroke mRS.,,01_stroke_synth.py,ordinal (proportional odds),1
patient_bg.csv,care_need,integer,grade,0–5,Long-term care need grade (JP scale).,,01_stroke_synth.py,ordinal,2
patient_bg.csv,hypertension,binary,,"0,1",History of hypertension.,,01_stroke_synth.py,logistic (intercept-calibrated),1
patient_bg.csv,diabetes,binary,,"0,1",History of diabetes.,,01_stroke_synth.py,logistic,0
patient_bg.csv,dyslipidemia,binary,,"0,1",History of dyslipidemia.,,01_stroke_synth.py,logistic,1
patient_bg.csv,afib,binary,,"0,1",Atrial fibrillation.,,01_stroke_synth.py,logistic,0
patient_bg.csv,heart_failure,binary,,"0,1",Heart failure.,,01_stroke_synth.py,logistic,0
patient_bg.csv,prior_stroke,binary,,"0,1",Prior stroke.,,01_stroke_synth.py,logistic,0
patient_bg.csv,smoking,category,,"Never,Former,Current",Smoking status.,,01_stroke_synth.py,ordinal approx.,Former
patient_bg.csv,living_alone,binary,,"0,1",Lives alone.,,01_stroke_synth.py,logistic,0
patient_bg.csv,jcs_arrival,category,,"0,1,2,3,10,20,30,100,200,300",Japan Coma Scale at arrival.,,01_stroke_synth.py,ordinal,10
patient_bg.csv,family_history,binary,,"0,1",Family history of stroke/CVD (any).,,01_stroke_synth.py,logistic,0
patient_bg.csv,adm_antiplatelet,binary,,"0,1",On antiplatelet at admission.,,01_stroke_synth.py,logistic,1
patient_bg.csv,adm_anticoagulant,binary,,"0,1",On anticoagulant at admission.,,01_stroke_synth.py,logistic,0
patient_bg.csv,adm_antihypertensive,binary,,"0,1",On antihypertensive at admission.,,01_stroke_synth.py,logistic,1
patient_bg.csv,adm_statin,binary,,"0,1",On statin at admission.,,01_stroke_synth.py,logistic,1
patient_bg.csv,acute_therapy,category,,Conservative therapy only; Intervenous t-PA only; Endovascular treatment only; t-PA + endovascular treatment,Acute therapy category.,,01_stroke_synth.py,categorical sampling,Conservative therapy only
patient_bg.csv,swallow_screen_24h,binary,,"0,1",Swallow screening within 24h.,,01_stroke_synth.py,logistic,1
patient_bg.csv,early_mobilization_48h,binary,,"0,1",Early mobilization within 48h.,,01_stroke_synth.py,logistic,1
patient_bg.csv,icu_admit,binary,,"0,1",ICU admission.,,01_stroke_synth.py,logistic,0
patient_bg.csv,icu_days,float,days,0–30,ICU length of stay (0 if not admitted).,,01_stroke_synth.py,gamma + rounding,1.5
patient_bg.csv,antithrombotic_day2,binary,,"0,1",Antithrombotic use on day 2.,,01_stroke_synth.py,logistic + override by contraindications,1
patient_bg.csv,enteral_feeding,binary,,"0,1",Enteral feeding in hospital.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_sICH,binary,,"0,1",Symptomatic intracranial hemorrhage.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_pneumonia,binary,,"0,1",Pneumonia in hospital.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_UTI,binary,,"0,1",Urinary tract infection.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_DVT,binary,,"0,1",Deep vein thrombosis.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_delirium,binary,,"0,1",Delirium.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_pressure_ulcer,binary,,"0,1",Pressure ulcer.,,01_stroke_synth.py,logistic,0
patient_bg.csv,comp_GI_bleed,binary,,"0,1",Gastrointestinal bleeding.,,01_stroke_synth.py,logistic,0
patient_bg.csv,event_fall_in_hospital,binary,,"0,1",Fall event in hospital.,,01_stroke_synth.py,logistic,0
patient_bg.csv,nihss_24h,float,score,0–42,NIHSS at 24h.,,01_stroke_synth.py,baseline NIHSS minus improvement,5.0
patient_bg.csv,nihss_day7,float,score,0–42,NIHSS at day 7.,,01_stroke_synth.py,24h NIHSS minus improvement,4.0
patient_bg.csv,rehab_start_day,integer,day index,1–21,Day rehabilitation started.,,01_stroke_synth.py,log-normal-like + clipping,3
patient_bg.csv,oac_planned_by_discharge,binary,,"0,1",OAC planned by discharge (esp. AF).,,01_stroke_synth.py,rule based on AF,1
patients_df.csv,patient_id,string,,,Unique patient identifier.,,03_stroke_outcomes.py,from input,P000123
patients_df.csv,severity_score_S,float,arbitrary,,Composite severity score (higher=worse).,,03_stroke_outcomes.py,weighted linear combination,2.3
patients_df.csv,comp_inhosp_death,binary,,"0,1",In-hospital death.,,03_stroke_outcomes.py,logistic draw,0
patients_df.csv,los_days,integer,days,>=4,Length of stay (negative binomial).,,03_stroke_outcomes.py,NB draw,13
patients_df.csv,discharge_destination,category,,"home,rehab_hospital,acute transfer,nursing_facility,death",Normalized discharge disposition.,,03_stroke_outcomes.py,multinomial logistic + normalization,home
patients_df.csv,mrs_discharge,integer,score,0–6,mRS at discharge (6=death).,,03_stroke_outcomes.py,latent threshold + override on death,3
patients_df.csv,readmit_30d,binary,,"0,1",30-day readmission.,,03_stroke_outcomes.py,logistic draw,0
patients_df.csv,mrs_90d,integer,score,0–6,mRS at 90 days (6=death).,,03_stroke_outcomes.py,discharge mRS + delta,2
nurse_features.csv,nurse_id,string,,,Unique nurse identifier.,,02_nurse_features.py,formatted,N0001
nurse_features.csv,role,category,,RN,Role (registered nurse).,,02_nurse_features.py,fixed,RN
nurse_features.csv,education,category,,"Diploma/ADN,BSN,MSN+",Highest nursing education.,,02_nurse_features.py,categorical sampling,BSN
nurse_features.csv,primary_unit,category,,general_med,Primary unit (fixed in demo).,,02_nurse_features.py,fixed,general_med
nurse_features.csv,years_experience,integer,years,0–40,Clinical experience years.,,02_nurse_features.py,log-normal + round/clip,7
nurse_features.csv,benner_level,category,,"novice,advanced_beginner,competent,proficient,expert",Benner skill acquisition level.,,02_nurse_features.py,rule from years,competent
nurse_features.csv,shift_type,category,,"day,evening,night,rotating",Typical shift type.,,02_nurse_features.py,categorical sampling,day
nurse_features.csv,workload_style,category,,"task_focused,patient_centered,by_the_book,adaptive",Workload style.,,02_nurse_features.py,categorical sampling,patient_centered
nurse_features.csv,communication_style,category,,"supportive,directive,informational,motivational",Communication style.,,02_nurse_features.py,categorical sampling,supportive
nurse_features.csv,speech_pace_wpm,integer,wpm,110–200,Speech pace adjusted by style.,,02_nurse_features.py,normal + bias + clip,145
nurse_features.csv,certifications,string,,comma-separated tokens,Comma-separated certifications (BLS + optional).,,02_nurse_features.py,independent draws per token,"BLS,ACLS,wound_care"
nurse_features.csv,O_openeness,float,0–1,,Big Five: Openness (note: field name has one 'n' as in code).,,02_nurse_features.py,MVN draw + clip,0.61
nurse_features.csv,C_conscientiousness,float,0–1,,Big Five: Conscientiousness.,,02_nurse_features.py,MVN draw + clip,0.63
nurse_features.csv,E_extraversion,float,0–1,,Big Five: Extraversion.,,02_nurse_features.py,MVN draw + clip,0.47
nurse_features.csv,A_agreeableness,float,0–1,,Big Five: Agreeableness.,,02_nurse_features.py,MVN draw + clip,0.69
nurse_features.csv,N_neuroticism,float,0–1,,Big Five: Neuroticism.,,02_nurse_features.py,MVN draw + clip,0.38
nurse_features.csv,empathy_trait,float,0–1,,Empathy (trait).,,02_nurse_features.py,normal + clip,0.72
nurse_features.csv,assertiveness_trait,float,0–1,,Assertiveness (trait).,,02_nurse_features.py,normal + clip,0.50
nurse_features.csv,patience_trait,float,0–1,,Patience (trait).,,02_nurse_features.py,normal + clip,0.66
nurse_features.csv,teaching_skill,float,0–1,,Teaching skill.,,02_nurse_features.py,normal + clip,0.63
nurse_features.csv,teach_back_usage_prob,float,0–1,,Probability of using teach-back.,,02_nurse_features.py,normal + clip,0.55
nurse_features.csv,mi_proficiency,float,0–1,,Motivational Interviewing proficiency.,,02_nurse_features.py,trait-weighted + noise,0.62
nurse_features.csv,communication_style_alignment,float,0–1,,Alignment between traits and chosen style.,,02_nurse_features.py,trait-style mapping,0.68
nurse_features.csv,burnout_risk,category,,"low,medium,high",Burnout risk category.,,02_nurse_features.py,rule from shift & Benner,medium
patient_nurse_pairs.csv,patient_id,string,,,Unique patient identifier.,,04_pair_patients_nurses.py,from outcomes CSV,P000123
patient_nurse_pairs.csv,los_days,integer,days,>=1,Length of stay carried from outcomes.,,04_pair_patients_nurses.py,from outcomes CSV,12
patient_nurse_pairs.csv,severity0,float,0–1,,Latent baseline severity (higher worse).,,04_pair_patients_nurses.py,"Beta(2,5)",0.42
patient_nurse_pairs.csv,social_barrier,float,0–1,,Latent social barrier.,,04_pair_patients_nurses.py,"Beta(2,6)",0.28
patient_nurse_pairs.csv,recovery_potential,float,0–1,,Latent recovery potential.,,04_pair_patients_nurses.py,"Normal(0.6,0.15) clipped",0.71
patient_nurse_pairs.csv,comp_inhosp_death,integer,,"0,1,NA",In-hospital death (from outcomes).,,04_pair_patients_nurses.py,pass-through,0
patient_nurse_pairs.csv,mrs_discharge,integer,score,"0–6,NA",mRS at discharge.,,04_pair_patients_nurses.py,pass-through,3
patient_nurse_pairs.csv,discharge_destination,category,,"home,rehab,transfer,snf,death",Discharge destination.,,04_pair_patients_nurses.py,pass-through,home
patient_nurse_pairs.csv,primary_nurse_id,string,,,Assigned primary nurse ID.,,04_pair_patients_nurses.py,load-balancing heuristic,N0042
patient_nurse_pairs.csv,primary_years_experience,integer,years,"0–40,NA",Primary nurse years of experience.,,04_pair_patients_nurses.py,from nurse_features,8
patient_nurse_pairs.csv,primary_benner_level,category,,"novice,advanced_beginner,competent,proficient,expert",Primary nurse Benner.,,04_pair_patients_nurses.py,from nurse_features,proficient
patient_nurse_pairs.csv,primary_care_quality,float,0–1,,Primary nurse care-quality score.,,04_pair_patients_nurses.py,weighted traits + caps,0.74
patient_nurse_pairs.csv,secondary_nurse_id,string,,,Assigned secondary nurse ID (or same as primary).,,04_pair_patients_nurses.py,load-balancing heuristic,N0101
patient_nurse_pairs.csv,secondary_years_experience,integer,years,"0–40,NA",Secondary nurse years of experience.,,04_pair_patients_nurses.py,from nurse_features,5
patient_nurse_pairs.csv,secondary_benner_level,category,,"novice,advanced_beginner,competent,proficient,expert",Secondary nurse Benner.,,04_pair_patients_nurses.py,from nurse_features,competent
patient_nurse_pairs.csv,secondary_care_quality,float,0–1,,Secondary nurse care-quality score.,,04_pair_patients_nurses.py,weighted traits + caps,0.61
dialogs_run/*.jsonl,patient_id,string,,,Patient identifier.,,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,from index,P000123
dialogs_run/*.jsonl,day,integer,day index,>=1,Hospital day number.,,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,from index,3
dialogs_run/*.jsonl,scene,string,,"wake,post_breakfast,pre_lunch,post_lunch,pre_dinner,lights_out,night",Scene identifier.,,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,fixed set,pre_dinner
dialogs_run/*.jsonl,scene_label,string,,ja-JP label,"Human-readable scene label (Japanese, demo).",,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,fixed set,pre_dinner
dialogs_run/*.jsonl,assignment,category,,"primary,secondary",Which nurse assignment for the scene.,,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,fixed set,secondary
dialogs_run/*.jsonl,clock_time,string,HH:MM,24h local time,Clock time for scene.,,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,fixed set,21:00
dialogs_run/*.jsonl,nurse_id,string,,,Nurse ID taking the scene.,,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,from index + assignment,N0042
dialogs_run/*.jsonl,conversation,array,,list of utterances,"List of utterance dictionaries (speaker, text, etc.).",,05_generate_dialogues_EN.py/05_generate_dialogues_JP.py/05_generate_dialogues_CN.py,from API output,"[{""speaker"":""Nurse"",""text"":""...""}, ...]"