{"schema_version":"papers/paper-detail-v1","title":"mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection","surface":"papers","opportunity_kernel":{"paper_id":"45a45768-903b-4fbb-91f3-fc40a7456953","title":"mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection","authors":["Dominik Macko"],"arxiv_id":"2605.02712v1","doi":null,"published_at":"2026-05-04T15:17:44.000Z","score_object":{"overall":{"value":4,"scale":"0-10","confidence":0.85,"confidence_reason":"Backfilled from persisted papers.viability_score.","model_version":"phase0-backfill-v1","pipeline_version":"phase0-kernel-v1","computed_at":"2026-05-05T20:09:49.049Z","fresh_until":"2026-06-04T20:09:49.049Z","is_stale":false,"source_count":1,"missingness":[]},"technical":{"value":1.4,"scale":"0-10","confidence":0.55,"confidence_reason":"Backfilled from paper_extraction_scorecards.reconstruction_score.","model_version":"phase0-backfill-v1","pipeline_version":"phase0-kernel-v1","computed_at":"2026-05-05T20:11:12.795Z","fresh_until":"2026-05-19T20:11:12.795Z","is_stale":true,"source_count":1,"missingness":["reproducibility_results.reproducibility_score","deployability_scores.score"]},"commercial":{"value":5,"scale":"0-10","confidence":0.75,"confidence_reason":"Backfilled from persisted commercial_flags and repo availability.","model_version":"phase0-backfill-v1","pipeline_version":"phase0-kernel-v1","computed_at":"2026-05-05T20:09:49.049Z","fresh_until":"2026-06-04T20:09:49.049Z","is_stale":false,"source_count":2,"missingness":[]},"market":{"value":5.5,"scale":"0-10","confidence":0.45,"confidence_reason":"Heuristic market score materialized from paper metadata, repo availability, and deployability.","model_version":"phase0-backfill-v1","pipeline_version":"phase0-kernel-v1","computed_at":"2026-05-05T20:30:25.846Z","fresh_until":"2026-05-19T20:30:25.846Z","is_stale":true,"source_count":1,"missingness":[]},"team":{"value":2.7,"scale":"0-10","confidence":0.42,"confidence_reason":"Heuristic fallback from paper author count and extracted affiliations.","model_version":"phase0-backfill-v1","pipeline_version":"phase0-kernel-v1","computed_at":"2026-05-05T20:09:49.049Z","fresh_until":"2026-05-19T20:09:49.049Z","is_stale":true,"source_count":2,"missingness":[]},"methodology":{"value":4.2,"scale":"0-10","confidence":0.82,"confidence_reason":"Backfilled from paper_extraction_scorecards.total_score.","model_version":"phase0-backfill-v1","pipeline_version":"phase0-kernel-v1","computed_at":"2026-05-05T20:11:12.795Z","fresh_until":"2026-06-04T20:11:12.795Z","is_stale":false,"source_count":2,"missingness":[]}},"evidence_receipt":{"freshness":"stale","proof_status":"unverified","repo_status":"active","references_count":0,"source_count":4,"coverage":0.6667,"missingness":["references","proof_status"],"unresolved_unknowns":["proof verification has not been recorded yet"],"last_verification_at":"2026-05-05T20:30:25.846Z"},"lineage_hash":"6ab11f3d84033683cc0840b712a362e73688093ee193a16329250edb45d75420"},"distribution":null,"replication_evidence":[],"author_dna":[]}