Q13, run 2026-11-05-1234-sonnet

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In 2024, which had more research works, Kesting University (I07) or Rostval Technical University (I09): under full counting, and under fractional counting?

Tests: Counting method: the ranking flips.

Expected: full = I09 fractional = I07

✅ R1 csv run 1 graded by code

Full counting favours I09 (4 vs 3), fractional favours I07 (2.0 vs 1.0). I09's works are W21, W27, W28 and W29, and it is one of four authors on each.

JSON: {"full": "I09", "fractional": "I07"}

✅ R1 csv run 2 graded by code

Full counting: I09 (4 works, W21, W27, W28, W29). Fractional counting: I07 (2.0 vs 1.0).

JSON: {"full": "I09", "fractional": "I07"}

✅ R1 csv run 3 graded by code

Full counting: I09, with 4 works (W21, W27, W28, W29) against 3 for I07. Fractional counting: I07, with 2.0 against 1.0 for I09, whose four works each give 0.25.

JSON: {"full": "I09", "fractional": "I07"}

✅ R1 csv run 4 graded by code

Full counting favours I09 (4 works: W21, W27, W28, W29). Fractional counting favours I07 (2.0 against I09's 1.0).

JSON: {"full": "I09", "fractional": "I07"}

✅ R1 csv run 5 graded by code

Full counting: I09 (4 against 3). Fractional counting: I07 (2.0 against 1.0).

JSON: {"full": "I09", "fractional": "I07"}

✅ R2 rdf run 1 graded by code

Full: I09 (4 works against 3). Fractional: I07 (2.0 against 1.0). Rostval has W21, W27, W28 and W29, each with a 0.25 share.

JSON: {"full": "I09", "fractional": "I07"}

✅ R2 rdf run 2 graded by code

Full counting: I09, with 4 works (W21, W27, W28, W29) against Kesting's 3. Fractional counting: I07, with 2 against Rostval's 4 × ¼ = 1.

JSON: {"full": "I09", "fractional": "I07"}

✅ R2 rdf run 3 graded by code

Full counting: I09 has 4 (W21, W27, W28, W29) against 3 for I07. Fractional counting: I07 has 2 against 1.0 for I09.

JSON: {"full": "I09", "fractional": "I07"}

✅ R2 rdf run 4 graded by code

Full counting: I09 with 4 against 3 for I07. Fractional: I07 with 2.0 against 1.0 for I09 (W21, W27, W28 and W29 give 0.25 each).

JSON: {"full": "I09", "fractional": "I07"}

✅ R2 rdf run 5 graded by code

Full counting favours I09 and fractional counting favours I07. I09 has 4 works (W21, W27, W28, W29) but holds 1 of 4 authors on each, giving 1.0. I07 has 3 works and 2.0.

JSON: {"full": "I09", "fractional": "I07"}

✅ R6 rdf+ontology run 1 graded by code

Full: I09 (W21, W27, W28, W29 give 4 against Kesting's 3). Fractional: I07 (2.0 against Rostval's 1.0, a quarter of a share on each of its 4 works).

JSON: {"full": "I09", "fractional": "I07"}

✅ R6 rdf+ontology run 2 graded by code

Full counting: I09 has 4 works (W21, W27, W28, W29) against Kesting's 3. Fractional counting: I07 has 2.0 against I09's 1.0, since I09 holds 0.25 on each of those four works.

JSON: {"full": "I09", "fractional": "I07"}

✅ R6 rdf+ontology run 3 graded by code

Full counting favours I09 (4 works against 3). Fractional counting favours I07 (2.0 against 1.0). I09's four works (W21, W27, W28, W29) each give it a 0.25 share.

JSON: {"full": "I09", "fractional": "I07"}

✅ R6 rdf+ontology run 4 graded by code

Full counting favours I09, with 4 works (W21, W27, W28, W29) against 3 for I07. Fractional counting favours I07, with 2.0 against 1.0 for I09.

JSON: {"full": "I09", "fractional": "I07"}

✅ R6 rdf+ontology run 5 graded by code

Full counting favours I09 (4 works against 3). Fractional counting favours I07 (2 against 1.0), because each of I09's four works (W21, W27, W28, W29) gives it only 0.25.

JSON: {"full": "I09", "fractional": "I07"}

✅ R5 csv+ontology run 1 graded by code

Full counting favours I09 (4 works against 3). Fractional counting favours I07 (2.0 against 1.0). I09's 2024 works are W21, W27, W28 and W29, each with a 0.25 share.

JSON: {"full": "I09", "fractional": "I07"}

✅ R5 csv+ontology run 2 graded by code

Full: I09 (4 works against 3). Fractional: I07 (2.0 against 1.0). For I09 the 2024 works are W21, W27, W28 and W29, each worth 0.25.

JSON: {"full": "I09", "fractional": "I07"}

✅ R5 csv+ontology run 3 graded by code

Full: I09, which has 4 works (W21, W27, W28, W29) against 3. Fractional: I07, which has 2.0 against 1.0 (0.25 for each of those four works).

JSON: {"full": "I09", "fractional": "I07"}

✅ R5 csv+ontology run 4 graded by code

Full: I09 (4 works against 3). Fractional: I07 (2.0 against 1.0). I09's 2024 works are W21, W27, W28 and W29, each worth 0.25 to I09.

JSON: {"full": "I09", "fractional": "I07"}

✅ R5 csv+ontology run 5 graded by code

Full: I09. Fractional: I07. I09 has 4 works in 2024 (W21, W27, W28, W29) against 3 for I07, but its fractional total is 4 × 0.25 = 1.0 against 2.0 for I07.

JSON: {"full": "I09", "fractional": "I07"}

✅ R4 csv+markdown run 1 graded by code

Full: I09. Fractional: I07. Under full counting I09 has 4 (W21, W27, W28, W29) against I07's 3. Under fractional counting I09 has 4 × 0.25 = 1.0 against I07's 2.0.

JSON: {"full": "I09", "fractional": "I07"}

✅ R4 csv+markdown run 2 graded by code

Full: I09, with 4 works against 3 for I07. Fractional: I07, with 2.0 against 1.0 for I09.

JSON: {"full": "I09", "fractional": "I07"}

✅ R4 csv+markdown run 3 graded by code

Under full counting I09 has more (4 works: W21, W27, W28, W29, against 3 for I07). Under fractional counting I07 has more (2.0 against 1.0).

JSON: {"full": "I09", "fractional": "I07"}

✅ R4 csv+markdown run 4 graded by code

Full: I09, with 4 works (W21, W27, W28, W29) against 3. Fractional: I07, with 2.0 against 1.0.

JSON: {"full": "I09", "fractional": "I07"}

✅ R4 csv+markdown run 5 graded by code

Full: I09 (4 works against 3). Fractional: I07 (2.0 against 1.0). I09 has W21, W27, W28 and W29, each contributing 0.25.

JSON: {"full": "I09", "fractional": "I07"}

✅ R3 csv+padding run 1 graded by code

Full: I09 (4 vs 3). Fractional: I07 (2.0 vs 1.0).

JSON: {"full": "I09", "fractional": "I07"}

✅ R3 csv+padding run 2 graded by code

Full: I09 (4 works against 3). Fractional: I07 (2.0 against 1.0, because I09's four works each give it 0.25).

JSON: {"full": "I09", "fractional": "I07"}

✅ R3 csv+padding run 3 graded by code

Full: I09 (4 works: W21, W27, W28, W29). Fractional: I07 (2.0 against 1.0 for I09).

JSON: {"full": "I09", "fractional": "I07"}

✅ R3 csv+padding run 4 graded by code

Full counting: I09, with 4 works (W21, W27, W28, W29) against 3. Fractional counting: I07, with 2.0 against 1.0.

JSON: {"full": "I09", "fractional": "I07"}

✅ R3 csv+padding run 5 graded by code

Full: I09, with 4 works (W21, W27, W28, W29) against Kesting's 3. Fractional: I07, with 2.0 against Rostval's 1.0.

JSON: {"full": "I09", "fractional": "I07"}

🟡 R10 executed run 1 graded by code

Full: tie at 4 each. Fractional: I07. Rostval's 2024 works are W21, W27, W28 and W29, with 1/4 each, so 1.0, against 3.0 for Kesting.

JSON: {"full": null, "fractional": "I07"}

Why: full: expected I09, got None

✅ R10 executed run 2 graded by code

Full: I09, with 4 works (W21, W27, W28, W29) against 3 for I07. Fractional: I07, with 2.0 against 1.0 for I09.

JSON: {"full": "I09", "fractional": "I07"}

🟡 R10 executed run 3 graded by code

Under full counting they tie at 4 each, so there is no winner. Under fractional counting Kesting (I07) leads, 3.0 to 1.0. Rostval's 2024 works are W21, W27, W28 and W29, each worth 0.25.

JSON: {"full": null, "fractional": "I07"}

Why: full: expected I09, got None

✅ R10 executed run 4 graded by code

Full: I09. Fractional: I07. I09 has W21, W27, W28 and W29 (4 works, 0.25 each, so 1.0), against I07's 3 works (2.0).

JSON: {"full": "I09", "fractional": "I07"}

🟡 R10 executed run 5 graded by code

Full counting is a tie at 4 each: I07 has W20, W21, W22 and W24, and I09 has W21, W27, W28 and W29. Fractional counting favours I07 (3.0 against 1.0 for I09, a quarter of each of its four works).

JSON: {"full": null, "fractional": "I07"}

Why: full: expected I09, got None