Datasets:
row_id
string | series_id
string | ph_rank
int64 | organism
string | strain_id
string | antibiotic_name
string | antibiotic_class
string | ph_value
float64 | exposure_index
float64 | mic_mg_L
float64 | cfu0_log10
float64 | cfu24_log10
float64 | kill_24_log10
float64 | media
string | assay_method
string | source_type
string | ph_decay_signal
int64 | earliest_ph_decay
int64 | notes
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ABXPD010-TR-0001
|
S1
| 1
|
Escherichia coli
|
EC-ATCC25922
|
azithromycin
|
macrolide
| 7
| 1
| 2
| 7.2
| 5.2
| 2
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
reference pH
|
ABXPD010-TR-0002
|
S1
| 2
|
Escherichia coli
|
EC-ATCC25922
|
azithromycin
|
macrolide
| 7.4
| 1
| 2
| 7.2
| 5.1
| 2.1
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
stable
|
ABXPD010-TR-0003
|
S1
| 3
|
Escherichia coli
|
EC-ATCC25922
|
azithromycin
|
macrolide
| 6.8
| 1
| 2
| 7.2
| 5.3
| 1.9
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
small drift
|
ABXPD010-TR-0004
|
S1
| 4
|
Escherichia coli
|
EC-ATCC25922
|
azithromycin
|
macrolide
| 6.5
| 1
| 2
| 7.2
| 5.35
| 1.85
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
still acceptable
|
ABXPD010-TR-0005
|
S1
| 5
|
Escherichia coli
|
EC-ATCC25922
|
azithromycin
|
macrolide
| 6
| 1
| 2
| 7.2
| 5.6
| 1.6
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
low pH weaker but not collapse
|
ABXPD010-TR-0006
|
S2
| 1
|
Pseudomonas aeruginosa
|
PA-CLIN120
|
tobramycin
|
aminoglycoside
| 7
| 1
| 1
| 7.3
| 5.2
| 2.1
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
reference pH
|
ABXPD010-TR-0007
|
S2
| 2
|
Pseudomonas aeruginosa
|
PA-CLIN120
|
tobramycin
|
aminoglycoside
| 7.4
| 1
| 1
| 7.3
| 5.25
| 2.05
|
CAMHB
|
ph_time_kill
|
simulated
| 0
| 0
|
stable
|
ABXPD010-TR-0008
|
S2
| 3
|
Pseudomonas aeruginosa
|
PA-CLIN120
|
tobramycin
|
aminoglycoside
| 6.8
| 1
| 1
| 7.3
| 6.1
| 1.2
|
CAMHB
|
ph_time_kill
|
simulated
| 1
| 1
|
collapse in physiologic low edge
|
ABXPD010-TR-0009
|
S2
| 4
|
Pseudomonas aeruginosa
|
PA-CLIN120
|
tobramycin
|
aminoglycoside
| 6.5
| 1
| 1
| 7.3
| 6.4
| 0.9
|
CAMHB
|
ph_time_kill
|
simulated
| 1
| 0
|
collapse persists
|
ABXPD010-TR-0010
|
S2
| 5
|
Pseudomonas aeruginosa
|
PA-CLIN120
|
tobramycin
|
aminoglycoside
| 6
| 1
| 1
| 7.3
| 6.6
| 0.7
|
CAMHB
|
ph_time_kill
|
simulated
| 1
| 0
|
worse at low pH
|
ABX-PD-010 pH-Dependent Activity Decay
Purpose
Detect collapse of antibiotic killing across physiologic pH.
Core idea
Use pH 7.0 as a reference inside each series.
Flag decay when killing drops sharply at pH values that still occur in vivo.
Physiologic window used in v1
- 6.8 to 7.6
Files
- data/train.csv
- data/test.csv
- scorer.py
Schema
Each row is one pH condition.
Required columns
- row_id
- series_id
- ph_rank
- organism
- strain_id
- antibiotic_name
- antibiotic_class
- ph_value
- exposure_index
- mic_mg_L
- cfu0_log10
- cfu24_log10
- kill_24_log10
- media
- assay_method
- source_type
- ph_decay_signal
- earliest_ph_decay
Labels
ph_decay_signal
- 1 for rows at or after the first detected collapse
earliest_ph_decay
- 1 only for the first detected row in that series
Scorer logic in v1
- require a single reference row at pH 7.0
- call decay when
- pH is inside 6.8 to 7.6
- kill drops by 0.8 log10 or more vs reference
- exposure_index stays within 10 percent of reference
- MIC stays within 2 fold of reference
Evaluation
Run
- python scorer.py --path data/test.csv
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