Q37, run 2026-11-04-1752-haiku

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Which institution is W70 credited to?

Tests: Local rule: only the affiliation listed last counts.

Expected: institution = I06

❌ R1 csv run 1 graded by code

The data credits W70 to two institutions: I04 (affil_seq 1) and I06 (affil_seq 2), both under A08. I have given I04 as the primary one, but this field is ambiguous.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R1 csv run 2 graded by code

I04 (Tessel Laboratory). W70 lists I04 as affiliation 1 and I06 as affiliation 2, so the data gives two; I04 is the primary one.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R1 csv run 3 graded by code

I04. W70's first affiliation (affil_seq 1) is I04, and I06 is its second.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R1 csv run 4 graded by code

I04 (affil_seq 1). W70 is also credited to I06 (affil_seq 2), which the question's singular wording does not cover.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R1 csv run 5 graded by code

I04 (Tessel Laboratory), the first affiliation. W70 also carries a second affiliation to I06.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R2 rdf run 1 graded by code

I04 (affiliationSeq 1). W70 is also credited to I06 (affiliationSeq 2).

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R2 rdf run 2 graded by code

I04 and I06. W70 has two affiliation records, AS-W70-A08-1 (I04) and AS-W70-A08-2 (I06).

JSON: {"institution": "I04, I06"}

Why: institution: expected I06, got I04, I06

❌ R2 rdf run 3 graded by code

I04 (affiliationSeq 1). W70 is also credited to I06 (affiliationSeq 2).

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R2 rdf run 4 graded by code

I04 (Tessel Laboratory), but W70 is also credited to I06 (Halloran), both via A08. The data gives two affiliations, so one institution cannot be singled out.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R2 rdf run 5 graded by code

I04 (Tessel Laboratory), via affiliation sequence 1 of A08. Affiliation 2 is I06 (Halloran).

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

✅ R6 rdf+ontology run 1 graded by code

I06. The last-listed affiliation on W70 is seq 2, Halloran Institute for Coastal Studies.

JSON: {"institution": "I06"}

✅ R6 rdf+ontology run 2 graded by code

I06. W70's second affiliation (seq 2) is I06, which is the one credited.

JSON: {"institution": "I06"}

✅ R6 rdf+ontology run 3 graded by code

I06. Its last-listed affiliation is seq 2, the Halloran Institute.

JSON: {"institution": "I06"}

✅ R6 rdf+ontology run 4 graded by code

I06. A08's last-listed affiliation on W70 is I06 (sequence 2).

JSON: {"institution": "I06"}

✅ R6 rdf+ontology run 5 graded by code

I06. W70's last affiliation (sequence 2) is I06.

JSON: {"institution": "I06"}

✅ R5 csv+ontology run 1 graded by code

I06. W70 lists I04 (seq 1) and I06 (seq 2), and only the last-listed affiliation counts.

JSON: {"institution": "I06"}

✅ R5 csv+ontology run 2 graded by code

I06. For W70, A08's last-listed affiliation (seq 2) is I06, so I04 is ignored.

JSON: {"institution": "I06"}

✅ R5 csv+ontology run 3 graded by code

I06. A08's last-listed affiliation on W70 is I06, the highest sequence number.

JSON: {"institution": "I06"}

✅ R5 csv+ontology run 4 graded by code

I06. W70's author A08 gave two affiliations, and the last-listed (seq 2) is I06.

JSON: {"institution": "I06"}

✅ R5 csv+ontology run 5 graded by code

I06. W70's author A08 lists two affiliations, and the later one (seq 2) is I06.

JSON: {"institution": "I06"}

✅ R4 csv+markdown run 1 graded by code

I06. The author A08 lists I04 at seq 1 and I06 at seq 2, and only the last-listed affiliation counts.

JSON: {"institution": "I06"}

✅ R4 csv+markdown run 2 graded by code

I06. W70's author A08 lists I04 (seq 1) and I06 (seq 2), and only the last-listed affiliation counts.

JSON: {"institution": "I06"}

✅ R4 csv+markdown run 3 graded by code

I06. W70's last-listed affiliation is seq 2, which is I06 (Halloran Institute).

JSON: {"institution": "I06"}

✅ R4 csv+markdown run 4 graded by code

I06. W70 lists I04 at affiliation sequence 1 and I06 at sequence 2, and only the last-listed affiliation counts.

JSON: {"institution": "I06"}

✅ R4 csv+markdown run 5 graded by code

I06. A08's last-listed affiliation on W70 is I06.

JSON: {"institution": "I06"}

❌ R3 csv+padding run 1 graded by code

I04 (Tessel Laboratory), its affil_seq 1. The same author on W70 is also credited to I06 (Halloran) at affil_seq 2.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R3 csv+padding run 2 graded by code

I04 and I06. A08 is credited to both on W70, so the singular question has two answers.

JSON: {"institution": "I04 and I06"}

Why: institution: expected I06, got I04 and I06

❌ R3 csv+padding run 3 graded by code

I04 (Tessel Laboratory), with affil_seq 1. The same author also lists I06 at affil_seq 2.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R3 csv+padding run 4 graded by code

I04. W70's author A08 lists I04 first (affil_seq 1) and I06 second (affil_seq 2).

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04

❌ R3 csv+padding run 5 graded by code

I04. W70's single author A08 has affil_seq 1 at I04 and seq 2 at I06, so I06 is the second affiliation.

JSON: {"institution": "I04"}

Why: institution: expected I06, got I04