{"closest_prior_art":[{"name":"Tesserae human-graded allusion benchmark","overlap":"Starts from a large search-generated set of textual parallels, has groups of human readers grade 3,400 source-target pairs on a five-level scale from no literary significance to pointed allusion, and models which similarities are meaningful.","remaining_difference":"It is an algorithm-evaluation benchmark, not an editorial promotion gate; the retained source does not describe registering every search variation and rejection, multiplicity-aware error control, prospective freezing, blinded matched-decoy adjudication, search-independent corroboration, or publication-status rules.","source_ids":["SRC1"]},{"name":"Independent annotation and retrieval evaluation for allusive text reuse","overlap":"Treats allusion discovery as information retrieval, uses independently working expert annotators, measures inter-annotator agreement, and demonstrates that defining the relevant passage is interpretive and materially affects retrieval.","remaining_difference":"Annotators delimit queries for previously identified allusions; they do not adjudicate intentionality blindly among matched decoys or calibrate promotion against the complete opportunity set of generated source-target pairings.","source_ids":["SRC2"]},{"name":"Structured intertext annotation using an intertextuality ontology and TEI provenance fields","overlap":"Provides structured representations of source-target relations and supports recording source, certainty, responsible party, relation specification, and mediator; it also distinguishes surface similarity from stronger, more intentional intertextual relations.","remaining_difference":"These representation standards do not prescribe a campaign registry, discovery-rate rule, frozen confirmation protocol, blind adjudication, corroboration threshold, or preservation of rejected candidates before publishing intentional-allusion language.","source_ids":["SRC3","SRC4"]}],"contrastive_claim_falsifier":"The remaining claim would be falsified by evidence that an existing editorial workflow already combines complete candidate-family and search-change logging, multiplicity-aware selection, frozen matched-decoy blinding, independent adjudication, and predeclared search-independent corroboration before intentional-allusion publication, or if a reconstruction pilot shows that applying those additions produces no reliable change in status calibration relative to ordinary reranking and expert grading.","contrastive_claim_remaining":"For source-target parallels generated from broad searches, a complete-family, multiplicity-aware promotion gate with frozen blinded adjudication and predeclared independent corroboration provides testable calibration beyond existing candidate ranking, expert grading, intertext ontologies, or TEI certainty and provenance metadata.","experiment_id":"eoa_inverse_innovation_exp13_second_slot_policy60_20260806","gates":{"adequate_source_search":{"rationale":"Four lanes covered the named intervention, older and synonymous terminology, operational tools and standards, and combinations of candidate generation, grading, provenance, blinding, and multiplicity. Four retained sources were opened and span four publishers or institutional hosts, including primary research and an official standard. Exact combination searches found adjacent components but no retained full workflow match.","source_ids":["SRC1","SRC2","SRC3","SRC4"],"status":"PASS"},"bounded_next_test":{"rationale":"The proposed shadow review is operationally bounded to at most 40 reconstructed pairings, two family definitions, one frozen focal candidate, matched decoys, three non-selecting readers, and delayed inspection of predefined corroboration. It can measure missing candidates, agreement, blinding failures, label changes, and burden without modifying public annotations. Prior work shows that human grading and inter-annotator studies are feasible comparators.","source_ids":["SRC1","SRC2"],"status":"PASS"},"distinct_testable_claim":{"rationale":"The proposal makes a separable claim: complete-family registration plus multiplicity-aware screening and frozen independent confirmation should change or better calibrate intentional-allusion promotions compared with evaluating only selected parallels. None of the retained adjacent practices contains that complete combination.","source_ids":["SRC1","SRC2","SRC3","SRC4"],"status":"PASS"},"no_obvious_safety_or_authority_stop":{"rationale":"The authorized first step is consensual, read-only, and leaves editorial, interpretive, and publication authority with the existing actors. It excludes deletion, public changes, premature access to reserved material, and intention-by-similarity, while specifying halts for provenance, confidentiality, recognition, and attribution failures.","source_ids":[],"status":"PASS"},"supported_problem":{"rationale":"Research directly reports that most textual similarities are not meaningful allusions, that thousands of candidate pairs require graded human assessment, and that allusive-reuse annotation is highly interpretive with low agreement. Theory and annotation work also separate surface similarity from intentional reference. The stronger claim that hidden search multiplicity already causes erroneous published annotations is not directly demonstrated, so support is partial but sufficient for this gate.","source_ids":["SRC1","SRC2","SRC3"],"status":"PASS"}},"prior_art_disposition":"ADJACENT_PRIOR_ART","problem_evidence":{"finding":"The problem is visible at the candidate-assessment level: broad text comparison generates many non-meaningful similarities, expert grading is required, query scope is interpretive, and annotator agreement can be low. The retained sources do not directly document a published intentional-allusion label caused by failure to preserve the full search opportunity set.","source_ids":["SRC1","SRC2","SRC3"],"status":"PARTLY_SUPPORTED"},"research_id":"eoa_inverse_innovation_exp13_light_screen_20260806","schema_version":1,"screen_id":"E13P135","screen_survival":true,"search_lanes":{"component_combination":{"no_result_note":"No retained source described the full combination of campaign-wide candidate registration, multiplicity-aware selection, frozen blinded matched decoys, and search-independent corroboration before editorial promotion.","queries":["\"allusion annotation\" \"false discovery rate\"","\"allusion detection\" multiplicity multiple comparisons","\"intertext\" candidate registry blinded adjudication","\"allusion\" matched decoys independent readers annotation"],"source_ids":["SRC1","SRC2","SRC3","SRC4"]},"direct_problem_and_intervention":{"no_result_note":"Direct searches found human grading and annotation-evaluation systems but no named Source-Parallel Promotion Gate or equivalent complete editorial workflow.","queries":["literary allusion detection false positives multiple comparisons candidate source passages human evaluation blinded decoys","Tesserae allusion detection benchmark human evaluation controls source text parallels","text reuse detection scholarly editions allusion candidate ranking annotation workflow"],"source_ids":["SRC1","SRC2"]},"products_practices_and_standards":{"no_result_note":null,"queries":["Tesserae literary allusion human benchmark false positive candidate ranking Coffee Forstall","digital scholarly edition annotation uncertainty provenance TEI cert resp source guidelines","site:tesserae.caset.buffalo.edu allusion benchmark scoring known parallels controls"],"source_ids":["SRC1","SRC4"]},"synonyms_and_historical_terms":{"no_result_note":null,"queries":["intertextuality detection annotation guidelines intentional allusion evidence source criticism","literary allusion criteria authorial intent source availability recurrence history interpretation scholarly","\"The Logic and Discovery of Textual Allusion\" full text","site:aclanthology.org allusive text reuse annotation interpretative benchmark"],"source_ids":["SRC2","SRC3"]}},"sources":[{"claims_supported":["Most textual similarities are not meaningful literary allusions.","Tesserae begins with a large set of parallels and uses human readers to distinguish meaningful allusions.","A benchmark of 3,400 sentence pairs was graded from 1 to 5 by student and faculty teams."],"publisher":"Digital Humanities 2013 conference; hosted by Walter J. Scheirer","source_id":"SRC1","source_type":"PRIMARY_RESEARCH","title":"Modelling the Interpretation of Literary Allusion with Machine Learning Techniques","url":"https://www.wjscheirer.com/projects/language-literature/coffee-et-al-abstract-dh2013.pdf"},{"claims_supported":["Allusive text reuse is difficult to detect because evidence may contain few or no shared words.","Benchmark construction is impeded by the interpretive character of annotation.","An independent-annotator study found low agreement, while manually defined queries improved retrieval."],"publisher":"Association for Computational Linguistics","source_id":"SRC2","source_type":"PRIMARY_RESEARCH","title":"On the Feasibility of Automated Detection of Allusive Text Reuse","url":"https://aclanthology.org/W19-2514/"},{"claims_supported":["Intertextuality can be represented as graded rather than binary, including dimensions of intentionality, explicitness, and selectivity.","Large-scale syntactic or semantic similarity does not capture all literary-theoretical aspects of intertextuality.","The proposed ontology structures source-target references, relation specifications, and mediators for manual annotation and automated reasoning."],"publisher":"Digital Humanities Quarterly","source_id":"SRC3","source_type":"PRIMARY_RESEARCH","title":"Systems of Intertextuality: Towards a Formalization of Text Relations for Manual Annotation and Automated Reasoning","url":"https://dhq.digitalhumanities.org/vol/17/3/000731/000731.html"},{"claims_supported":["TEI provides standard attributes for an annotation's source, certainty, and responsible party.","Certainty can be represented categorically or probabilistically.","TEI supports explicit identifiers, source links, and detailed responsibility statements but does not itself impose the proposed confirmation gate."],"publisher":"TEI Consortium","source_id":"SRC4","source_type":"OFFICIAL_STANDARD","title":"TEI P5 Guidelines, Chapter 1: The TEI Infrastructure","url":"https://www.tei-c.org/release/doc/tei-p5-doc/en/html/ST.html"}],"world_novelty_boundary":"This bounded public-web screen establishes only that the retained sources are adjacent rather than a close match to the complete proposal. It cannot establish world novelty, patentability, market size, expert acceptance, implementation feasibility beyond the bounded pilot, or realized scholarly value; unindexed editorial manuals, paywalled literature, local project procedures, and unpublished workflows may contain closer practice."}