{"id":"W134362049","doi":"","title":"Modeling Language Acquisition at Multiple Temporal Scales","year":2000,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Verb; Context (archaeology); Representation (politics); Linguistics; Computer science; Noun; Argument (complex analysis); Artificial intelligence; Natural language processing; Cognitive science; Psychology; Cognitive psychology; History","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001052745,0.0004851556,0.0004951297,0.0006806552,0.0003783009,0.001711364,0.001031521,0.001183826,0.003712805],"category_scores_gemma":[0.005726404,0.0006940981,0.001033484,0.0006305141,0.0009887966,0.002902291,0.001766734,0.001683979,0.0005410825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00185939,"about_ca_system_score_gemma":0.00117066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02452246,"about_ca_topic_score_gemma":0.01910499,"domain_scores_codex":[0.9996374,0.0001216763,0.00001923067,0.00009609154,0.00005838349,0.00006732889],"domain_scores_gemma":[0.9979887,0.001237771,0.0002710768,0.0001269023,0.0001995573,0.0001760027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000112572,0.00006927601,0.006819068,0.00006145938,0.00008519251,0.0002196026,0.000338495,0.8759733,0.00251683,0.0916872,0.0009475517,0.02116945],"study_design_scores_gemma":[0.000007288006,0.00001322796,0.0007065665,0.000006627634,0.00001052943,0.00002153744,0.00002737449,0.9759396,0.0001386526,0.0224168,0.0007028289,0.000008809712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4031731,0.001329805,0.5671724,0.002461306,0.0001067258,0.00007492931,0.0006080853,0.0007330514,0.02434053],"genre_scores_gemma":[0.9198239,0.0006461257,0.06749877,0.0001236274,0.00005306474,0.0001287801,0.0002581122,0.0001304513,0.01133722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02452246,"threshold_uncertainty_score":0.04875946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388182625061344,"score_gpt":0.2121777749374974,"score_spread":0.1982959486868839,"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."}}