| --- |
| license: mit |
| language: |
| - en |
| pretty_name: ABX-PD-005 Time-Kill Curve Shape Distortion |
| tags: |
| - antibiotics |
| - pharmacodynamics |
| - resistance |
| - time-kill |
| - tabular |
| task_categories: |
| - tabular-classification |
| size_categories: |
| - n<1k |
| --- |
| |
| # ABX-PD-005: Time-Kill Curve Shape Distortion |
|
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| This dataset tests whether you can detect loss of log linear kill coherence. |
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| The curve stops behaving like a clean log linear decline. |
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| It becomes plateaued or multiphasic. |
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| ## Time grid |
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| v1 uses |
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| - 0, 2, 4, 6, 24 hours |
|
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| ## Files |
|
|
| - data/train.csv |
| - data/test.csv |
| - scorer.py |
|
|
| ## Schema |
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| Each row is one timepoint in a time kill series. |
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| Required columns |
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| - row_id |
| - series_id |
| - timepoint_h |
| - organism |
| - strain_id |
| - antibiotic_name |
| - antibiotic_class |
| - drug_conc_mg_L |
| - cfu_log10 |
| - media |
| - assay_method |
| - source_type |
| - shape_distortion_signal |
| - earliest_distortion |
| |
| ## Labels |
| |
| - shape_distortion_signal |
| - 1 for rows at or after distortion |
| |
| - earliest_distortion |
| - 1 only for the first detected row in that series |
|
|
| ## Evaluation |
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| Run |
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| - python scorer.py --path data/test.csv |
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| The scorer detects distortion using |
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| - plateau segments |
| - multiphasic sign changes in slopes |
| - poor linear fit |
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| The scorer avoids a common mistake. |
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| It does not call distortion when drug concentration changes too much. |
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|
