{"id":"W2066308621","doi":"10.1075/is.13.1.06jen","title":"The biology of language and the epigenesis of recursive embedding","year":2012,"lang":"en","type":"article","venue":"Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Simon Fraser University","keywords":"Generative grammar; Recursion (computer science); Grammar; Cognitive science; Frame (networking); Predicate (mathematical logic); Epistemology; Linguistics; Computer science; Philosophy; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001031865,0.00004842399,0.00016477,0.00001428148,0.0007497706,0.00001879959,0.00007087089,0.00006570257,0.000003036311],"category_scores_gemma":[0.0002490126,0.00002378911,0.0000274045,0.00007870336,0.001138397,0.00007342116,0.00007657787,0.00007746742,3.34325e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001940467,"about_ca_system_score_gemma":0.000003970587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003410861,"about_ca_topic_score_gemma":0.0007761557,"domain_scores_codex":[0.9987115,0.0008262691,0.0002501269,0.00005874705,0.000051559,0.0001018554],"domain_scores_gemma":[0.9989332,0.0007284606,0.0001865262,0.00005382899,0.00008158253,0.00001641529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000222168,0.00008297891,0.1401163,0.00001516332,0.00007341708,1.111679e-7,0.396438,6.829386e-7,0.001858696,0.420903,0.00005444134,0.04023516],"study_design_scores_gemma":[0.00018527,0.0000334288,0.03912948,0.00003749766,0.00002647577,0.000001262605,0.9565385,0.00001074688,0.0001400757,0.002371434,0.001459853,0.00006599238],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709839,0.02707445,0.000005261828,0.001236878,0.0001558367,0.0001622591,0.000003791932,0.000004705138,0.0003729072],"genre_scores_gemma":[0.9920648,0.007769014,0.000005212074,0.00001045508,0.00008908554,0.0000331419,0.000002293833,0.000001085303,0.00002486963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5601005,"threshold_uncertainty_score":0.5766705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1115661554743853,"score_gpt":0.4250353393113153,"score_spread":0.3134691838369301,"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."}}