{
  "version": 1,
  "model": "Source-1",
  "fitted_on": "a held-out validation split of 9,744 chunks (documents never trained on), against the labels of the teacher, an open-weight 27B LLM scoring the 13-field rubric; nothing here was fitted on evaluation labels",
  "drop_line": {
    "line": "toxicity >= 4 or spam_seo >= 3.5 or boilerplate >= 4.5",
    "meaning": "keep is false when this expression is true on a chunk's or a document's scores. It is the schema's default hard filters (schema_default) with the spam_seo threshold lowered from 4 to 3.5. source1.py applies it by default (drop_line=\"default\" applies schema_default instead).",
    "schema_default": "toxicity >= 4 or spam_seo >= 4 or boilerplate >= 4.5",
    "rule": "the candidate with the highest drop recall among those whose keep agreement with the teacher's keep flags is at least 0.95",
    "reference": "the teacher's keep flags: schema_default applied to the teacher's labels of each validation chunk",
    "columns": {
      "keep_agreement": "share of chunks where the line and the teacher make the same keep decision",
      "drop_recall": "share of the teacher's drops the line also drops",
      "teacher_drops": "chunks the teacher drops",
      "caught": "of those, chunks the line drops too",
      "wrong_drops": "chunks the line drops but the teacher keeps",
      "line_drops": "chunks the line drops",
      "drop_share": "share of all chunks the line drops"
    },
    "candidates": [
      {
        "line": "toxicity >= 4 or spam_seo >= 4 or boilerplate >= 4.5",
        "keep_agreement": 0.96,
        "drop_recall": 0.7111,
        "teacher_drops": 1042,
        "caught": 741,
        "wrong_drops": 89,
        "line_drops": 830,
        "drop_share": 0.0852
      },
      {
        "line": "toxicity >= 4 or spam_seo >= 3.5 or boilerplate >= 4.5",
        "keep_agreement": 0.9638,
        "drop_recall": 0.7706,
        "teacher_drops": 1042,
        "caught": 803,
        "wrong_drops": 114,
        "line_drops": 917,
        "drop_share": 0.0941
      },
      {
        "line": "toxicity >= 4 or spam_seo >= 3 or boilerplate >= 4.5",
        "keep_agreement": 0.929,
        "drop_recall": 0.8301,
        "teacher_drops": 1042,
        "caught": 865,
        "wrong_drops": 515,
        "line_drops": 1380,
        "drop_share": 0.1416
      },
      {
        "line": "toxicity >= 4 or spam_seo >= 2.5 or boilerplate >= 4.5",
        "keep_agreement": 0.8559,
        "drop_recall": 0.8724,
        "teacher_drops": 1042,
        "caught": 909,
        "wrong_drops": 1271,
        "line_drops": 2180,
        "drop_share": 0.2237
      },
      {
        "line": "toxicity >= 4 or spam_seo >= 3.5 or boilerplate >= 4",
        "keep_agreement": 0.9453,
        "drop_recall": 0.88,
        "teacher_drops": 1042,
        "caught": 917,
        "wrong_drops": 408,
        "line_drops": 1325,
        "drop_share": 0.136
      }
    ]
  },
  "offsets_meaning": "per quality score: mean teacher label minus mean Source-1 score over the validation chunks; added to Source-1's score, an offset removes its average lean against the teacher. All are below 0.02 in absolute value, so source1.py reports the model's own scores unless apply_offsets=True.",
  "offsets": {
    "educational_value": {
      "offset": -0.00264963054187195,
      "chunks": 9744,
      "mean_teacher": 1.9859,
      "mean_source1": 1.9886
    },
    "reasoning_depth": {
      "offset": -0.005093390804597586,
      "chunks": 9744,
      "mean_teacher": 1.5808,
      "mean_source1": 1.5859
    },
    "writing_quality": {
      "offset": -0.009194376026272266,
      "chunks": 9744,
      "mean_teacher": 2.9367,
      "mean_source1": 2.9459
    },
    "information_density": {
      "offset": -0.005678571428571644,
      "chunks": 9744,
      "mean_teacher": 2.485,
      "mean_source1": 2.4907
    },
    "reliability": {
      "offset": -0.01612294745484366,
      "chunks": 9744,
      "mean_teacher": 3.1512,
      "mean_source1": 3.1673
    }
  }
}