{"id":"W1852496846","doi":"10.1111/tops.12211","title":"The Latent Structure of Dictionaries","year":2016,"lang":"en","type":"article","venue":"Topics in Cognitive Science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; University of Ottawa","funders":"","keywords":"Rest (music); Word (group theory); Computer science; Core (optical fiber); Set (abstract data type); Categorization; Vertex (graph theory); Artificial intelligence; Natural language processing; Graph; Mathematics; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002925514,0.00004997361,0.00005261228,0.00007451072,0.0001585469,0.00006646138,0.000904486,0.00002130205,0.000003670513],"category_scores_gemma":[0.0006712569,0.00002374619,0.00001240586,0.0005592161,0.0008009927,0.00045796,0.0002911538,0.00006944018,0.000001009264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003682735,"about_ca_system_score_gemma":0.0001177375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007981781,"about_ca_topic_score_gemma":0.00001882251,"domain_scores_codex":[0.9992144,0.0000200283,0.0001128305,0.000196374,0.0002939828,0.0001623799],"domain_scores_gemma":[0.9992688,0.0002152961,0.00006064388,0.0001869482,0.0002459833,0.000022291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003888139,0.000009415831,0.004975567,0.000003023217,0.000001378322,0.000003026101,0.0003866485,1.356662e-7,0.02484477,0.4601533,0.00001940554,0.5095995],"study_design_scores_gemma":[0.0001408476,0.00004467272,0.01983372,0.0001194587,0.000001119433,0.000007457065,0.0000290213,0.0002670633,0.4272234,0.551919,0.000322464,0.00009172584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1605844,0.00132371,0.8287452,0.006667634,0.0006862595,0.0002612007,0.00001158281,0.0001814876,0.001538461],"genre_scores_gemma":[0.9677778,0.00002309997,0.0319344,0.0000764336,0.00001948226,0.0000022854,5.816313e-8,0.000001173612,0.0001652145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8071935,"threshold_uncertainty_score":0.2951291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782947085291535,"score_gpt":0.3011776556249314,"score_spread":0.283348184772016,"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."}}