Datasets:
row_id string | series_id string | timepoint_h int64 | organism string | strain_id string | drug_a string | drug_b string | stress_index float64 | synergy_score float64 | expected_synergy_score float64 | synergy_gap float64 | monoA_mic_mg_L float64 | monoB_mic_mg_L float64 | monoA_resistant_cutoff_mg_L float64 | monoB_resistant_cutoff_mg_L float64 | media string | assay_method string | source_type string | synergy_decay_signal int64 | earliest_synergy_decay int64 | notes string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ABXCT001-TR-0001 | S1 | 0 | Escherichia coli | EC-CLIN101 | cefepime | amikacin | 0.1 | 0.8 | 0.8 | 0 | 1 | 2 | 16 | 64 | CAMHB | checkerboard | simulated | 0 | 0 | baseline |
ABXCT001-TR-0002 | S1 | 6 | Escherichia coli | EC-CLIN101 | cefepime | amikacin | 0.85 | 0.78 | 0.8 | 0.02 | 1 | 2 | 16 | 64 | CAMHB | checkerboard | simulated | 0 | 0 | stable |
ABXCT001-TR-0003 | S1 | 12 | Escherichia coli | EC-CLIN101 | cefepime | amikacin | 0.9 | 0.45 | 0.8 | 0.35 | 1 | 2 | 16 | 64 | CAMHB | checkerboard | simulated | 1 | 1 | synergy drops early mono stable |
ABXCT001-TR-0004 | S1 | 24 | Escherichia coli | EC-CLIN101 | cefepime | amikacin | 0.9 | 0.4 | 0.8 | 0.4 | 2 | 2 | 16 | 64 | CAMHB | checkerboard | simulated | 1 | 0 | synergy still low mono within 2x |
ABXCT001-TR-0005 | S1 | 48 | Escherichia coli | EC-CLIN101 | cefepime | amikacin | 0.9 | 0.3 | 0.8 | 0.5 | 32 | 2 | 16 | 64 | CAMHB | checkerboard | simulated | 1 | 0 | monoA crosses later |
ABXCT001-TR-0006 | S2 | 0 | Pseudomonas aeruginosa | PA-CLIN220 | piperacillin_tazobactam | ciprofloxacin | 0.1 | 0.75 | 0.75 | 0 | 2 | 0.25 | 64 | 4 | CAMHB | checkerboard | simulated | 0 | 0 | baseline |
ABXCT001-TR-0007 | S2 | 24 | Pseudomonas aeruginosa | PA-CLIN220 | piperacillin_tazobactam | ciprofloxacin | 0.85 | 0.7 | 0.75 | 0.05 | 2 | 0.25 | 64 | 4 | CAMHB | checkerboard | simulated | 0 | 0 | no decay |
ABXCT001-TR-0008 | S2 | 48 | Pseudomonas aeruginosa | PA-CLIN220 | piperacillin_tazobactam | ciprofloxacin | 0.9 | 0.68 | 0.75 | 0.07 | 2 | 0.25 | 64 | 4 | CAMHB | checkerboard | simulated | 0 | 0 | stable |
ABXCT001-TR-0009 | S3 | 0 | Staphylococcus aureus | SA-CLIN330 | vancomycin | rifampin | 0.1 | 0.78 | 0.78 | 0 | 1 | 0.03 | 8 | 1 | CAMHB | checkerboard | simulated | 0 | 0 | baseline |
ABXCT001-TR-0010 | S3 | 12 | Staphylococcus aureus | SA-CLIN330 | vancomycin | rifampin | 0.9 | 0.2 | 0.78 | 0.58 | 1 | 0.03 | 8 | 1 | CAMHB | checkerboard | simulated | 0 | 0 | one point only keep v1 strict |
ABX-CT-001 Synergy Score Decay
Purpose
Detect loss of combination synergy before monotherapy resistance appears.
Core pattern
- stress_index high
- synergy_gap rises and stays high
- mono MICs stay below cutoffs during the early window
- later at least one mono MIC crosses its cutoff
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_a
- drug_b
- stress_index
- synergy_score
- expected_synergy_score
- synergy_gap
- monoA_mic_mg_L
- monoB_mic_mg_L
- monoA_resistant_cutoff_mg_L
- monoB_resistant_cutoff_mg_L
- media
- assay_method
- source_type
- synergy_decay_signal
- earliest_synergy_decay
Labels
synergy_decay_signal
- 1 for rows at or after the first confirmed synergy decay point
earliest_synergy_decay
- 1 only for the first detected decay row in that series
Scorer logic in v1
- baseline is timepoint 0
- candidate decay point
- stress_index at least 0.80
- synergy_gap at least 0.30 at two consecutive timepoints
- mono MICs below cutoffs and no more than 2x baseline
- exclude synergy_gap drop spike then snapback artifacts
- confirmation
- later monoA or monoB MIC crosses its cutoff
Evaluation
Run
- python scorer.py --path data/test.csv
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