Datasets:
row_id
string | series_id
string | treatment_day
int64 | host_model
string | drug
string | duration_exposure_index
float64 | total_dose_mg
int64 | expected_total_dose_mg
int64 | dose_deviation
float64 | eos_percent
float64 | expected_eos_percent
float64 | eos_rise_vs_expected
float64 | tryptase_ng_mL
float64 | expected_tryptase_ng_mL
float64 | tryptase_rise_vs_expected
float64 | immune_coherence_index
float64 | host_stress_index
float64 | later_hypersensitivity_flag
int64 | assay_method
string | source_type
string | allergic_sensitization_signal
int64 | earliest_allergic_sensitization
int64 | notes
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ABXHT007-TR-0001
|
S1
| 0
|
human_sim
|
amoxicillin
| 0.1
| 0
| 0
| 0
| 2
| 2
| 0
| 4
| 4
| 0
| 0.9
| 0.1
| 0
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
baseline
|
ABXHT007-TR-0002
|
S1
| 3
|
human_sim
|
amoxicillin
| 0.85
| 1,500
| 1,500
| 0
| 2.2
| 2.2
| 0
| 4.1
| 4.1
| 0
| 0.88
| 0.9
| 0
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
tracks expected
|
ABXHT007-TR-0003
|
S1
| 5
|
human_sim
|
amoxicillin
| 0.9
| 2,500
| 2,500
| 0
| 6
| 2.3
| 3.7
| 10
| 4.2
| 5.8
| 0.35
| 0.9
| 0
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
first divergence
|
ABXHT007-TR-0004
|
S1
| 6
|
human_sim
|
amoxicillin
| 0.9
| 3,000
| 3,000
| 0
| 6.5
| 2.3
| 4.2
| 11
| 4.2
| 6.8
| 0.3
| 0.9
| 0
|
cbc_tryptase_panel
|
simulated
| 1
| 1
|
onset
|
ABXHT007-TR-0005
|
S1
| 8
|
human_sim
|
amoxicillin
| 0.9
| 4,000
| 4,000
| 0
| 8
| 2.4
| 5.6
| 18
| 4.3
| 13.7
| 0.2
| 0.9
| 1
|
cbc_tryptase_panel
|
simulated
| 1
| 0
|
hypersensitivity later
|
ABXHT007-TR-0006
|
S2
| 0
|
human_sim
|
cefazolin
| 0.1
| 0
| 0
| 0
| 2.1
| 2.1
| 0
| 4
| 4
| 0
| 0.9
| 0.1
| 0
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
baseline
|
ABXHT007-TR-0007
|
S2
| 5
|
human_sim
|
cefazolin
| 0.9
| 5,000
| 5,000
| 0
| 2.4
| 2.3
| 0.1
| 4.2
| 4.1
| 0.1
| 0.86
| 0.9
| 0
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
stable
|
ABXHT007-TR-0008
|
S2
| 10
|
human_sim
|
cefazolin
| 0.9
| 10,000
| 10,000
| 0
| 2.5
| 2.4
| 0.1
| 4.2
| 4.2
| 0
| 0.84
| 0.9
| 0
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
stable
|
ABXHT007-TR-0009
|
S3
| 0
|
human_sim
|
amoxicillin
| 0.9
| 0
| 0
| 0
| 7
| 7
| 0
| 4
| 4
| 0
| 0.9
| 0.9
| 1
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
baseline eos high
|
ABXHT007-TR-0010
|
S4
| 6
|
human_sim
|
amoxicillin
| 0.9
| 3,000
| 3,000
| 0
| 6.5
| 2.3
| 4.2
| 11
| 4.2
| 6.8
| 0.3
| 0.3
| 1
|
cbc_tryptase_panel
|
simulated
| 0
| 0
|
stress low
|
ABX-HT-007 Allergic Sensitization Pattern
Purpose
Detect early allergic sensitization when immune response markers stop tracking treatment duration before hypersensitivity events.
Core pattern
- host_stress_index high
- duration_exposure_index high
- immune_coherence_index drops
- eos_rise_vs_expected or tryptase_rise_vs_expected stays high
- later_hypersensitivity_flag appears
Files
- data/train.csv
- data/test.csv
- scorer.py
Schema
Each row is one timepoint in a within series treatment course.
Required columns
- row_id
- series_id
- treatment_day
- host_model
- drug
- duration_exposure_index
- total_dose_mg
- expected_total_dose_mg
- dose_deviation
- eos_percent
- expected_eos_percent
- eos_rise_vs_expected
- tryptase_ng_mL
- expected_tryptase_ng_mL
- tryptase_rise_vs_expected
- immune_coherence_index
- host_stress_index
- later_hypersensitivity_flag
- assay_method
- source_type
- allergic_sensitization_signal
- earliest_allergic_sensitization
Labels
allergic_sensitization_signal
- 1 for rows at or after first confirmed sensitization onset
earliest_allergic_sensitization
- 1 only for the first onset row in that series
Scorer logic in v1
- exclude series with high baseline eosinophils
- candidate onset point
- host_stress_index at least 0.80
- duration_exposure_index at least 0.80
- immune_coherence_index at most 0.40
- eos_rise_vs_expected at least 3.0 or tryptase_rise_vs_expected at least 5.0
- for two consecutive points
- ignore one point eosinophil spike then recovery artifacts
- confirmation
- later_hypersensitivity_flag equals 1 later in series
Evaluation
Run
- python scorer.py --path data/test.csv
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