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row_id
string
series_id
string
timepoint_h
int64
organism
string
strain_id
string
drug_name
string
resistant_subpop_frac
float64
mic_drug_mg_L
float64
resistant_mic_cutoff_mg_L
float64
media
string
assay_method
string
source_type
string
hetero_shift_signal
int64
earliest_hetero_shift
int64
notes
string
ABXRM007-TR-0001
S1
0
Klebsiella pneumoniae
KP-CLIN101
colistin
0.01
0.5
4
CAMHB
pap_heteroresistance
simulated
0
0
baseline
ABXRM007-TR-0002
S1
12
Klebsiella pneumoniae
KP-CLIN101
colistin
0.04
0.5
4
CAMHB
pap_heteroresistance
simulated
0
0
minor rise
ABXRM007-TR-0003
S1
24
Klebsiella pneumoniae
KP-CLIN101
colistin
0.18
1
4
CAMHB
pap_heteroresistance
simulated
1
1
minor threshold crossed
ABXRM007-TR-0004
S1
48
Klebsiella pneumoniae
KP-CLIN101
colistin
0.72
8
4
CAMHB
pap_heteroresistance
simulated
1
0
dominance and MIC crosses
ABXRM007-TR-0005
S2
0
Staphylococcus aureus
SA-CLIN220
vancomycin
0.02
1
8
CAMHB
pap_heteroresistance
simulated
0
0
baseline
ABXRM007-TR-0006
S2
24
Staphylococcus aureus
SA-CLIN220
vancomycin
0.03
1
8
CAMHB
pap_heteroresistance
simulated
0
0
stable
ABXRM007-TR-0007
S2
48
Staphylococcus aureus
SA-CLIN220
vancomycin
0.05
1
8
CAMHB
pap_heteroresistance
simulated
0
0
no shift
ABXRM007-TR-0008
S3
0
Acinetobacter baumannii
AB-CLIN330
imipenem
0.01
0.5
8
CAMHB
pap_heteroresistance
simulated
0
0
baseline
ABXRM007-TR-0009
S3
12
Acinetobacter baumannii
AB-CLIN330
imipenem
0.9
0.5
8
CAMHB
pap_heteroresistance
simulated
0
0
spike candidate
ABXRM007-TR-0010
S3
24
Acinetobacter baumannii
AB-CLIN330
imipenem
0.02
0.5
8
CAMHB
pap_heteroresistance
simulated
0
0
snapback artifact

ABX-RM-007 Heteroresistance Population Shift

Purpose

Detect growth of a minor resistant subpopulation before it becomes dominant and before MIC crosses the resistant cutoff.

Core pattern

  • resistant_subpop_frac crosses a minor threshold
  • MIC stays below resistant_mic_cutoff_mg_L at that time
  • later resistant_subpop_frac becomes dominant
  • later MIC crosses resistant_mic_cutoff_mg_L

Files

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

Schema

Each row is one timepoint in a within strain series.

Required columns

  • row_id
  • series_id
  • timepoint_h
  • organism
  • strain_id
  • drug_name
  • resistant_subpop_frac
  • mic_drug_mg_L
  • resistant_mic_cutoff_mg_L
  • media
  • assay_method
  • source_type
  • hetero_shift_signal
  • earliest_hetero_shift

Labels

  • hetero_shift_signal

    • 1 for rows at or after the first confirmed shift point
  • earliest_hetero_shift

    • 1 only for the first detected shift row in that series

Scorer logic in v1

  • baseline is timepoint 0
  • candidate early shift point
    • resistant_subpop_frac at least 0.20
    • MIC at most 2x baseline
    • MIC still below resistant cutoff
    • exclude spike then snapback artifacts
  • confirmation
    • later resistant_subpop_frac reaches at least 0.70
    • later MIC crosses resistant cutoff

Evaluation

Run

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