{"id":"W7113104903","doi":"","title":"Identifying alternations in historical corpus data: the genitive alternation in Old English","year":2025,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Alternation (linguistics); Genitive case; Noun phrase; Determiner; Old English; Noun","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002554119,0.0002392594,0.0002867455,0.004541789,0.001286892,0.001517243,0.0005267271,0.0003519058,0.002187572],"category_scores_gemma":[0.01067584,0.0002173869,0.0001614937,0.006330418,0.001478936,0.001831132,0.001471844,0.000693247,0.0005292214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008723214,"about_ca_system_score_gemma":0.0006771507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009187194,"about_ca_topic_score_gemma":0.02991893,"domain_scores_codex":[0.9987698,0.00033766,0.0002419076,0.0003191768,0.0002459621,0.00008545406],"domain_scores_gemma":[0.9906624,0.005071208,0.001137316,0.00146212,0.001461803,0.0002051907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009127154,0.0002025644,0.4064435,0.002663488,0.0002300586,0.004445843,0.131565,0.002056348,0.05605136,0.04613564,0.01513983,0.3341537],"study_design_scores_gemma":[0.00005172737,0.0001560356,0.7551114,0.0004377196,0.0002351627,0.002954056,0.02497669,0.006401601,0.02093724,0.01200418,0.176561,0.0001731375],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9517413,0.002665707,0.02528368,0.0004537005,0.000148968,0.0000966163,0.007469487,0.0002358882,0.01190468],"genre_scores_gemma":[0.9733933,0.0005544553,0.01612755,0.00007701568,0.00005706903,0.0001257763,0.007692907,0.0001738677,0.00179816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009187194,"threshold_uncertainty_score":0.01826745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06936281419802982,"score_gpt":0.2841782684504474,"score_spread":0.2148154542524176,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}