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ClarusC64/ABX-RM-004_porin_loss_synchronization-v0.1

ABX-RM-004 Porin Loss Synchronization Purpose Detect a coordinated shift toward low porin states across the population before MIC shifts. Core pattern low_porin_frac rises porin_cv drops permeability_index_rel drops mic_cefepime_mg_L stays near baseline during the shift mic_cefepime_mg_L rises later 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 porin_marker… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ABX-RM-004_porin_loss_synchronization-v0.1.

sourceHugging Facemitupdated 8mo agoView on Hugging Face
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ABX-RM-004 Porin Loss Synchronization

Purpose

Detect a coordinated shift toward low porin states across the population before MIC shifts.

Core pattern

  • —lowporinfrac rises
  • —porin_cv drops
  • —permeabilityindexrel drops
  • —miccefepimemg_L stays near baseline during the shift
  • —miccefepimemg_L rises later

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
  • —porin_marker
  • —porinmeanrel
  • —porin_cv
  • —lowporinfrac
  • —permeabilityindexrel
  • —miccefepimemg_L
  • —media
  • —assay_method
  • —source_type
  • —porinsyncsignal
  • —earliestporinsync

Labels

  • —porinsyncsignal
  • —1 for rows at or after the first confirmed synchronization point
  • —earliestporinsync
  • —1 only for the first detected synchronization row in that series

Scorer logic in v1

  • —baseline is timepoint 0
  • —candidate synchronization event
  • —lowporinfrac rises by 0.30 or more
  • —porin_cv drops by 0.15 or more
  • —permeabilityindexrel drops by 20 percent or more
  • —MIC during the shift no more than 2x baseline
  • —exclude spike then snapback artifacts
  • —confirmation
  • —later MIC reaches at least 4x baseline

Evaluation

Run

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