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README.md

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+---
+pretty_name: CAD-TCM
+license: cc-by-4.0
+configs:
+  - config_name: default
+    data_files: data.csv
+language:
+  - en
+task_categories:
+  - tabular-classification
+task_ids:
+  - tabular-multi-class-classification
+size_categories:
+  - 100K<n<1M
+tags:
+  - anomaly-detection
+  - continual-learning
+  - continual-anomaly-detection
+  - predictive-maintenance
+  - steel-manufacturing
+  - tandem-cold-mill
+  - tabular
+  - synthetic
+---
+
+# CAD-TCM
+
+## Dataset Summary
+
+**CAD-TCM** is a single-source continual anomaly detection benchmark scenario for predictive maintenance in steel manufacturing. It is derived from **TCM: Benchmark Datasets for Predictive Maintenance in Steel Manufacturing**, a synthetic dataset generated from a physics-based mathematical model of a 5-stand tandem cold mill (TCM), and converts the original tabular sensor data into a sequence of concept-grouped tasks.
+
+The dataset contains **108,872 samples**, **8 tasks**, and has a reported **18.66% anomaly ratio in the test set**.
+
+
+## Intended Use
+
+This dataset is intended for research on:
+
+- continual anomaly detection;
+- continual learning for tabular data;
+- predictive maintenance in industrial/manufacturing processes;
+- robustness under distribution shift;
+- task ordering in continual-learning benchmarks;
+- forgetting and knowledge transfer across related process-monitoring concepts;
+- benchmarking anomaly detectors under sequential task exposure.
+
+The intended use is **defensive/industrial machine learning research**, i.e. detecting equipment faults and process anomalies to support predictive maintenance.
+
+## Dataset Source
+
+- TCM: Benchmark Datasets for Predictive Maintenance in Steel Manufacturing: `https://zenodo.org/records/11469702`
+
+The source data is entirely **synthetic**, generated from a physics-based mathematical model of a 5-stand tandem cold mill simulating four fault types: reduction-scheme irregularities, work-roll friction increase, bearing failure (elevated motor torque), and motor efficiency loss.
+
+
+## Dataset Files
+
+The repository contains the following files:
+
+| File | Description |
+|---|---|
+| `data.csv` | Main tabular dataset file. |
+| `orderings.json` | Predefined task orderings for continual-learning evaluation. |
+| `croissant.json` | Croissant metadata describing the dataset. |
+
+## Dataset Structure
+
+The main file is:
+
+```text
+data.csv
+```
+
+The dataset contains task metadata, binary labels, and numerical rolling-mill process/sensor features.
+
+### Core Columns
+
+| Column | Type | Description |
+|---|---:|---|
+| `task_id` | integer | Numeric identifier of the continual-learning task. |
+| `task_name` | string | Name of the task, e.g. `tcm_0`. |
+| `task_split` | string | Split assignment for the row. |
+| `label` | integer | Binary anomaly label. `0` denotes normal operation and `1` denotes an anomalous/faulty condition. |
+
+### Task Identifiers
+
+The dataset contains the following task identifiers:
+
+`tcm_0`, `tcm_1`, `tcm_2`, `tcm_3`, `tcm_4`, `tcm_5`, `tcm_6`, `tcm_7`
+
+### Feature Columns
+
+The remaining columns are numerical process/sensor features from the 5-stand tandem cold mill, including per-stand measurements. Representative examples include:
+
+- `thickness_entry`, `thickness_exit`
+- `width`
+- `ys_entry`, `ys_exit` (yield strength)
+- `work_roll_diam_1` … `work_roll_diam_5`
+- `work_roll_mileage_1` … `work_roll_mileage_5`
+- `reduction_1` … `reduction_5`
+- `tension_0` … `tension_5`
+- `roll_speed_1` … `roll_speed_5`
+- `force_1` … `force_5`
+- `torque_1` … `torque_5`
+- `gap_1` … `gap_5`
+- `motor_power_1` … `motor_power_5`
+
+For the complete schema, see `croissant.json`.
+
+## Task Orderings
+
+The dataset provides six predefined orderings in `orderings.json`. These orderings define different continual-learning evaluation regimes over the same task set.
+
+| Ordering | Task sequence |
+|---|---|
+| `curriculum_asc` | `tcm_2` → `tcm_5` → `tcm_7` → `tcm_6` → `tcm_4` → `tcm_0` → `tcm_1` → `tcm_3` |
+| `curriculum_desc` | `tcm_3` → `tcm_1` → `tcm_0` → `tcm_4` → `tcm_6` → `tcm_7` → `tcm_5` → `tcm_2` |
+| `generalization_desc` | `tcm_0` → `tcm_5` → `tcm_2` → `tcm_7` → `tcm_4` → `tcm_6` → `tcm_1` → `tcm_3` |
+| `generalization_asc` | `tcm_3` → `tcm_1` → `tcm_6` → `tcm_4` → `tcm_7` → `tcm_2` → `tcm_5` → `tcm_0` |
+| `smooth_drift` | `tcm_5` → `tcm_7` → `tcm_0` → `tcm_2` → `tcm_1` → `tcm_6` → `tcm_4` → `tcm_3` |
+| `abrupt_drift` | `tcm_0` → `tcm_3` → `tcm_5` → `tcm_1` → `tcm_2` → `tcm_6` → `tcm_7` → `tcm_4` |
+
+These orderings are intended to expose complementary continual-learning dynamics, including curriculum-like adaptation, generalization-oriented ordering, smooth drift, and abrupt drift.
+
+## Dataset Creation
+The details of dataset creation can be found in our paper: [link](https://arxiv.org/abs/2607.18289)
+
+## Citation
+When using the dataset, please cite:
+```
+@article{faber2026towards,
+  title={Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios},
+  author={Faber, Kamil and Smendowski, Mateusz and Corizzo, Roberto},
+  journal={arXiv preprint arXiv:2607.18289},
+  year={2026}
+}
+```

croissant.json

@@ -0,0 +1,1004 @@
+{
+  "@context": {
+    "@language": "en",
+    "@vocab": "https://schema.org/",
+    "citeAs": "cr:citeAs",
+    "column": "cr:column",
+    "conformsTo": "dct:conformsTo",
+    "cr": "http://mlcommons.org/croissant/",
+    "rai": "http://mlcommons.org/croissant/RAI/",
+    "data": {
+      "@id": "cr:data",
+      "@type": "@json"
+    },
+    "dataType": {
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+    },
+    "dct": "http://purl.org/dc/terms/",
+    "equivalentProperty": "cr:equivalentProperty",
+    "examples": {
+      "@id": "cr:examples",
+      "@type": "@json"
+    },
+    "extract": "cr:extract",
+    "field": "cr:field",
+    "fileProperty": "cr:fileProperty",
+    "fileObject": "cr:fileObject",
+    "fileSet": "cr:fileSet",
+    "format": "cr:format",
+    "includes": "cr:includes",
+    "isLiveDataset": "cr:isLiveDataset",
+    "jsonPath": "cr:jsonPath",
+    "key": "cr:key",
+    "md5": "cr:md5",
+    "parentField": "cr:parentField",
+    "path": "cr:path",
+    "recordSet": "cr:recordSet",
+    "references": "cr:references",
+    "regex": "cr:regex",
+    "repeated": "cr:repeated",
+    "replace": "cr:replace",
+    "samplingRate": "cr:samplingRate",
+    "sc": "https://schema.org/",
+    "separator": "cr:separator",
+    "source": "cr:source",
+    "subField": "cr:subField",
+    "transform": "cr:transform"
+  },
+  "@type": "sc:Dataset",
+  "name": "CAD-TCM",
+  "description": "CAD-TCM is a continual anomaly detection benchmark scenario derived from the TCM dataset (Benchmark Datasets for Predictive Maintenance in Steel Manufacturing), which simulates a 5-stand tandem cold mill (TCM) using a physics-based mathematical model. The original synthetic sensor data is converted into a sequence of 8 concept-grouped tasks (tcm_0-tcm_7). The dataset contains 108,872 samples with an 18.66% anomaly ratio in the test set, covering four synthetic fault types: reduction-scheme irregularities, work-roll friction increase, bearing failure (elevated motor torque), and motor efficiency loss.",
+  "conformsTo": [
+    "http://mlcommons.org/croissant/1.1",
+    "http://mlcommons.org/croissant/RAI/1.0"
+  ],
+  "citeAs": "@misc{faber2026towards, title={Towards Principled Continual Anomaly Detection: A Systematic Framework and Benchmark Scenarios}, author={Faber, Kamil and Smendowski, Mateusz and Corizzo, Roberto}, year={2026}, eprint={2607.18289}, archivePrefix={arXiv}, primaryClass={cs.LG}, doi={10.48550/arXiv.2607.18289}, url={https://arxiv.org/abs/2607.18289}}",
+  "creator": [
+    {
+      "@type": "sc:Person",
+      "name": "Kamil Faber"
+    },
+    {
+      "@type": "sc:Person",
+      "name": "Roberto Corizzo"
+    }
+  ],
+  "inLanguage": "en",
+  "keywords": [
+    "predictive maintenance",
+    "steel manufacturing",
+    "tandem cold mill",
+    "anomaly-detection",
+    "continual-learning",
+    "continual-anomaly-detection",
+    "tabular"
+  ],
+  "license": "https://creativecommons.org/licenses/by/4.0/",
+  "prov:wasDerivedFrom": "https://zenodo.org/records/11469702",
+  "prov:wasGeneratedBy": "https://github.com/lifelonglab/CAD-Benchmarks-Framework",
+  "rai:dataBiases": "Data is entirely synthetic, generated from a physics-based simulation of a single mill configuration; it reflects only the four modeled fault types and does not capture the full distribution of real-world rolling-mill anomalies or plant-to-plant variability.",
+  "rai:dataLimitations": "Synthetic data generated via a mathematical model of a 5-stand tandem cold mill rather than measured from a real production line; it may not fully capture real sensor noise, calibration drift, or interactions between simultaneous real-world faults. Anomaly labels are limited to four synthetic fault classes (reduction-scheme irregularities, work-roll friction increase, bearing failure via elevated motor torque, and motor efficiency loss).",
+  "rai:dataSocialImpact": "Intended for industrial predictive-maintenance and defensive anomaly-detection research. Low misuse risk: the data represents synthetic process telemetry from a simulated rolling-mill process, not real plant operations or individuals.",
+  "rai:dataUseCases": [
+    "Training",
+    "Testing",
+    "Validation"
+  ],
+  "rai:hasSyntheticData": true,
+  "rai:personalSensitiveInformation": "No PII. All fields are synthetic physical process measurements (thickness, force, torque, speed, tension, motor power, roll diameter/mileage) produced by a mathematical simulation; no data was collected from real individuals or identifiable facilities.",
+  "url": "https://huggingface.co/datasets/lifelonglab/CAD-TCM",
+  "version": "1.0.0",
+  "distribution": [
+    {
+      "@type": "cr:FileObject",
+      "@id": "data.csv",
+      "name": "data.csv",
+      "description": "Tabular dataset rows.",
+      "contentSize": "47255844 B",
+      "contentUrl": "data.csv",
+      "encodingFormat": "text/csv",
+      "sha256": "9fecf011bd001607b110df4c7da715d6401070c1c75c8f90babb3fe716b00eee"
+    },
+    {
+      "@type": "cr:FileObject",
+      "@id": "orderings.json",
+      "name": "orderings.json",
+      "description": "Task orderings for continual-learning evaluation.",
+      "contentSize": "1442 B",
+      "contentUrl": "orderings.json",
+      "encodingFormat": "application/json",
+      "sha256": "4d11816b6840d391dc9102db5fdda7dfa55d3a160be4c2d23044b5b3fcedb4ec"
+    }
+  ],
+  "recordSet": [
+    {
+      "@type": "cr:RecordSet",
+      "@id": "data",
+      "name": "data",
+      "description": "Per-row records from data.csv with auto-inferred schema.",
+      "field": [
+        {
+          "@type": "cr:Field",
+          "@id": "data/thickness_entry",
+          "name": "thickness_entry",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "thickness_entry"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/thickness_exit",
+          "name": "thickness_exit",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "thickness_exit"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/width",
+          "name": "width",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "width"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/ys_entry",
+          "name": "ys_entry",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "ys_entry"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/ys_exit",
+          "name": "ys_exit",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "ys_exit"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_diam_1",
+          "name": "work_roll_diam_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_diam_1"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_diam_2",
+          "name": "work_roll_diam_2",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_diam_2"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_diam_3",
+          "name": "work_roll_diam_3",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_diam_3"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_diam_4",
+          "name": "work_roll_diam_4",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_diam_4"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_diam_5",
+          "name": "work_roll_diam_5",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_diam_5"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_mileage_1",
+          "name": "work_roll_mileage_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_mileage_1"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_mileage_2",
+          "name": "work_roll_mileage_2",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_mileage_2"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_mileage_3",
+          "name": "work_roll_mileage_3",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_mileage_3"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_mileage_4",
+          "name": "work_roll_mileage_4",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_mileage_4"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/work_roll_mileage_5",
+          "name": "work_roll_mileage_5",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "work_roll_mileage_5"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/reduction_1",
+          "name": "reduction_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "reduction_1"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/reduction_2",
+          "name": "reduction_2",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "reduction_2"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/reduction_3",
+          "name": "reduction_3",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "reduction_3"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/reduction_4",
+          "name": "reduction_4",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "reduction_4"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/reduction_5",
+          "name": "reduction_5",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "reduction_5"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/tension_0",
+          "name": "tension_0",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "tension_0"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/tension_1",
+          "name": "tension_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "tension_1"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/tension_2",
+          "name": "tension_2",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "tension_2"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/tension_3",
+          "name": "tension_3",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "tension_3"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/tension_4",
+          "name": "tension_4",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "tension_4"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/tension_5",
+          "name": "tension_5",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "tension_5"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/roll_speed_1",
+          "name": "roll_speed_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "roll_speed_1"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/roll_speed_2",
+          "name": "roll_speed_2",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "roll_speed_2"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/roll_speed_3",
+          "name": "roll_speed_3",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "roll_speed_3"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/roll_speed_4",
+          "name": "roll_speed_4",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "roll_speed_4"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/roll_speed_5",
+          "name": "roll_speed_5",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "roll_speed_5"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/force_1",
+          "name": "force_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
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+            }
+          }
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+          "name": "force_2",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/force_3",
+          "name": "force_3",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/force_4",
+          "name": "force_4",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
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+        },
+        {
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+          "@id": "data/force_5",
+          "name": "force_5",
+          "dataType": "sc:Float",
+          "source": {
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+              "@id": "data.csv"
+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/torque_1",
+          "name": "torque_1",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
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+          "name": "torque_2",
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+        {
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+          "@id": "data/torque_3",
+          "name": "torque_3",
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+            },
+            "extract": {
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+          }
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+        {
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+          "@id": "data/torque_4",
+          "name": "torque_4",
+          "dataType": "sc:Float",
+          "source": {
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+            },
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+          }
+        },
+        {
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+          "@id": "data/torque_5",
+          "name": "torque_5",
+          "dataType": "sc:Float",
+          "source": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/gap_1",
+          "name": "gap_1",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+          }
+        },
+        {
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+          "@id": "data/gap_2",
+          "name": "gap_2",
+          "dataType": "sc:Float",
+          "source": {
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+        {
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+          "@id": "data/gap_3",
+          "name": "gap_3",
+          "dataType": "sc:Float",
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+            "extract": {
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+          }
+        },
+        {
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+          "@id": "data/gap_4",
+          "name": "gap_4",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/gap_5",
+          "name": "gap_5",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/motor_power_1",
+          "name": "motor_power_1",
+          "dataType": "sc:Float",
+          "source": {
+            "fileObject": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/motor_power_2",
+          "name": "motor_power_2",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
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+          "@id": "data/motor_power_3",
+          "name": "motor_power_3",
+          "dataType": "sc:Float",
+          "source": {
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+            },
+            "extract": {
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+            }
+          }
+        },
+        {
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+          "@id": "data/motor_power_4",
+          "name": "motor_power_4",
+          "dataType": "sc:Float",
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+            },
+            "extract": {
+              "column": "motor_power_4"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/motor_power_5",
+          "name": "motor_power_5",
+          "dataType": "sc:Float",
+          "source": {
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+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "motor_power_5"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/label",
+          "name": "label",
+          "dataType": "sc:Integer",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "label"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/task_split",
+          "name": "task_split",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "task_split"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/task_id",
+          "name": "task_id",
+          "dataType": "sc:Integer",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "task_id"
+            }
+          }
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "data/task_name",
+          "name": "task_name",
+          "dataType": "sc:Text",
+          "source": {
+            "fileObject": {
+              "@id": "data.csv"
+            },
+            "extract": {
+              "column": "task_name"
+            }
+          }
+        }
+      ]
+    },
+    {
+      "@type": "cr:RecordSet",
+      "@id": "orderings",
+      "name": "orderings",
+      "description": "Task orderings for continual-learning evaluation. Inlined so the Croissant is self-contained.",
+      "key": {
+        "@id": "orderings/name"
+      },
+      "field": [
+        {
+          "@type": "cr:Field",
+          "@id": "orderings/name",
+          "name": "name",
+          "dataType": "sc:Text"
+        },
+        {
+          "@type": "cr:Field",
+          "@id": "orderings/task_sequence",
+          "name": "task_sequence",
+          "dataType": "sc:Text",
+          "references": {
+            "field": {
+              "@id": "data/task_name"
+            }
+          },
+          "repeated": true
+        }
+      ],
+      "data": [
+        {
+          "orderings/name": "curriculum_asc",
+          "orderings/task_sequence": [
+            "tcm_2",
+            "tcm_5",
+            "tcm_7",
+            "tcm_6",
+            "tcm_4",
+            "tcm_0",
+            "tcm_1",
+            "tcm_3"
+          ]
+        },
+        {
+          "orderings/name": "curriculum_desc",
+          "orderings/task_sequence": [
+            "tcm_3",
+            "tcm_1",
+            "tcm_0",
+            "tcm_4",
+            "tcm_6",
+            "tcm_7",
+            "tcm_5",
+            "tcm_2"
+          ]
+        },
+        {
+          "orderings/name": "generalization_desc",
+          "orderings/task_sequence": [
+            "tcm_0",
+            "tcm_5",
+            "tcm_2",
+            "tcm_7",
+            "tcm_4",
+            "tcm_6",
+            "tcm_1",
+            "tcm_3"
+          ]
+        },
+        {
+          "orderings/name": "generalization_asc",
+          "orderings/task_sequence": [
+            "tcm_3",
+            "tcm_1",
+            "tcm_6",
+            "tcm_4",
+            "tcm_7",
+            "tcm_2",
+            "tcm_5",
+            "tcm_0"
+          ]
+        },
+        {
+          "orderings/name": "smooth_drift",
+          "orderings/task_sequence": [
+            "tcm_5",
+            "tcm_7",
+            "tcm_0",
+            "tcm_2",
+            "tcm_1",
+            "tcm_6",
+            "tcm_4",
+            "tcm_3"
+          ]
+        },
+        {
+          "orderings/name": "abrupt_drift",
+          "orderings/task_sequence": [
+            "tcm_0",
+            "tcm_3",
+            "tcm_5",
+            "tcm_1",
+            "tcm_2",
+            "tcm_6",
+            "tcm_7",
+            "tcm_4"
+          ]
+        }
+      ]
+    }
+  ],
+  "datePublished": "2026-05-06"
+}