{"id":"W4303427410","doi":"10.1007/s11049-022-09553-2","title":"What learning Latin verbal morphology tells us about morphological theory","year":2022,"lang":"en","type":"article","venue":"Natural Language & Linguistic Theory","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Defense Science and Engineering Graduate; Army Research Office; University of Sheffield; National University of Singapore; York University; University of Pennsylvania","keywords":"Linguistics; Participle; Philosophy of language; Arbitrariness; Computer science; Set (abstract data type); Meaning (existential); Syncretism (linguistics); Epistemology; Morpheme; Verb; Sociology; Philosophy; Metaphysics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002891045,0.0002282582,0.0003404215,0.001108058,0.0008424954,0.004913501,0.0006710315,0.0007858108,0.008621024],"category_scores_gemma":[0.01486131,0.0002902751,0.0001920049,0.001120245,0.009070132,0.009995142,0.001796229,0.001733469,0.0006583103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312863,"about_ca_system_score_gemma":0.0006119582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008588384,"about_ca_topic_score_gemma":0.00120716,"domain_scores_codex":[0.9987152,0.0008457893,0.00004100032,0.0001974563,0.0001492128,0.00005147434],"domain_scores_gemma":[0.9886286,0.008658309,0.0006944492,0.001095812,0.0007264902,0.0001963746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002515847,0.0000744451,0.03456094,0.0002622032,0.00004893065,0.0006520959,0.04007486,0.001835814,0.003555428,0.8359574,0.002702552,0.08002369],"study_design_scores_gemma":[0.00002378097,0.00007823565,0.01643136,0.0002307135,0.00002225671,0.000531073,0.01964643,0.004823789,0.002506621,0.9217008,0.033955,0.00004994367],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7352307,0.001497513,0.05995038,0.01729844,0.0001707172,0.00002609595,0.0004546579,0.0002617352,0.1851096],"genre_scores_gemma":[0.9935522,0.0003043492,0.00395406,0.0002675774,0.00004831779,0.00001116694,0.0001256197,0.00007074371,0.001666015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008621024,"threshold_uncertainty_score":0.02884024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294108691654188,"score_gpt":0.2454812344787643,"score_spread":0.2325401475622224,"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."}}