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row_id
string
series_id
string
exposure_rank
int64
organism
string
strain_id
string
antibiotic_name
string
antibiotic_class
string
auc_24_mg_h_L
float64
mic_mg_L
float64
auc_mic_ratio
float64
cfu0_log10
float64
cfu24_log10
float64
kill_24_log10
float64
media
string
assay_method
string
source_type
string
decoupling_signal
int64
earliest_decoupling
int64
notes
string
ABXPD006-TR-0001
S1
1
Escherichia coli
EC-ATCC25922
levofloxacin
fluoroquinolone
40
0.25
160
7.2
5.2
2
CAMHB
auc_time_kill
simulated
0
0
baseline exposure
ABXPD006-TR-0002
S1
2
Escherichia coli
EC-ATCC25922
levofloxacin
fluoroquinolone
80
0.25
320
7.2
4.6
2.6
CAMHB
auc_time_kill
simulated
0
0
more killing with higher ratio
ABXPD006-TR-0003
S1
3
Escherichia coli
EC-ATCC25922
levofloxacin
fluoroquinolone
140
0.25
560
7.2
3.9
3.3
CAMHB
auc_time_kill
simulated
0
0
expected monotone gain
ABXPD006-TR-0004
S2
1
Klebsiella pneumoniae
KP-CLIN088
ceftriaxone
3rd_gen_cephalosporin
120
0.5
240
7.1
5.1
2
CAMHB
auc_time_kill
simulated
0
0
baseline
ABXPD006-TR-0005
S2
2
Klebsiella pneumoniae
KP-CLIN088
ceftriaxone
3rd_gen_cephalosporin
220
0.5
440
7.1
5.05
2.05
CAMHB
auc_time_kill
simulated
1
1
ratio up kill flat
ABXPD006-TR-0006
S2
3
Klebsiella pneumoniae
KP-CLIN088
ceftriaxone
3rd_gen_cephalosporin
360
0.5
720
7.1
5.2
1.9
CAMHB
auc_time_kill
simulated
1
0
ratio up kill worse
ABXPD006-TR-0007
S3
1
Staphylococcus aureus
SA-ATCC29213
vancomycin
glycopeptide
180
1
180
6.9
5.2
1.7
CAMHB
auc_time_kill
simulated
0
0
baseline
ABXPD006-TR-0008
S3
2
Staphylococcus aureus
SA-ATCC29213
vancomycin
glycopeptide
300
1
300
6.9
4.7
2.2
CAMHB
auc_time_kill
simulated
0
0
expected improvement
ABXPD006-TR-0009
S3
3
Staphylococcus aureus
SA-ATCC29213
vancomycin
glycopeptide
420
1
420
6.9
4.75
2.15
CAMHB
auc_time_kill
simulated
0
0
small variance
ABXPD006-TR-0010
S4
1
Escherichia coli
EC-CLIN501
meropenem
carbapenem
90
0.03
3,000
7.2
6.6
0.6
CAMHB
auc_time_kill
simulated
0
0
low kill despite high ratio single row

ABX-PD-006: AUC/MIC Ratio Decoupling

This dataset tests when AUC/MIC stops predicting bacterial killing.

The expected pattern is simple.

Higher AUC/MIC should produce more 24h killing.

Decoupling is when AUC/MIC rises but killing does not improve.

Files

  • data/train.csv
  • data/test.csv
  • scorer.py

Schema

Each row is one exposure condition in an ordered series.

Required columns

  • row_id
  • series_id
  • exposure_rank
  • organism
  • strain_id
  • antibiotic_name
  • antibiotic_class
  • auc_24_mg_h_L
  • mic_mg_L
  • auc_mic_ratio
  • cfu0_log10
  • cfu24_log10
  • kill_24_log10
  • media
  • assay_method
  • source_type
  • decoupling_signal
  • earliest_decoupling

Labels

  • decoupling_signal

    • 1 for rows at or after decoupling
  • earliest_decoupling

    • 1 only for the first detected row in that series

Evaluation

Run

  • python scorer.py --path data/test.csv

The scorer

  • checks ratio consistency
  • detects decoupling when ratio rises but kill does not
  • avoids false calls when baseline inoculum varies too much
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