{"id":"W2096979061","doi":"10.1017/s0305000904006622","title":"Large constituent families help children parse compounds","year":2005,"lang":"en","type":"article","venue":"Journal of Child Language","topic":"Language Development and Disorders","field":"Psychology","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Affect (linguistics); Lexicon; Psychology; Meaning (existential); Parsing; Linguistics; Analogy; Segmentation; Developmental psychology; Chemistry; Natural language processing; Communication; Artificial intelligence; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003633923,0.0001802914,0.00031385,0.0002236063,0.0001044281,0.00004068328,0.0002971709,0.00009491452,0.003318455],"category_scores_gemma":[0.0000471475,0.0001399784,0.000180225,0.0001501011,0.00007115279,0.0001719085,0.00004594066,0.0003425764,0.000317916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004029533,"about_ca_system_score_gemma":0.00004750513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003854651,"about_ca_topic_score_gemma":0.0001043463,"domain_scores_codex":[0.9986356,0.00007637026,0.0004890249,0.0001505097,0.0002970828,0.0003514359],"domain_scores_gemma":[0.9992249,0.00004667193,0.0003046633,0.0002265101,0.00006077137,0.0001364781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008062641,0.003393563,0.2138416,0.00003468746,0.002099449,0.001488733,0.1599501,0.00006520693,0.0006479749,0.02178904,0.5027981,0.09308534],"study_design_scores_gemma":[0.01539019,0.0003705904,0.4554622,0.0002179287,0.0002774912,0.004591065,0.04984942,0.00000976131,0.001594161,0.0001584399,0.4710146,0.001064118],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8808609,0.00749928,0.0002205192,0.001621116,0.0005410931,0.0001235635,0.00002503061,0.00003955967,0.1090689],"genre_scores_gemma":[0.9936093,0.00008402708,0.0004834752,0.003639429,0.0008617917,0.000002182961,0.00002580198,0.00002086052,0.001273112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2416207,"threshold_uncertainty_score":0.9975926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005737437596276991,"score_gpt":0.2675994268399669,"score_spread":0.2618619892436899,"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."}}