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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