{"id":"W886532087","doi":"","title":"Source of Individuation in Mandarin Chinese, a Classifier Language","year":2008,"lang":"en","type":"article","venue":"Pacific Asia Conference on Language, Information, and Computation","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mandarin Chinese; Noun; Linguistics; Computer science; Syntax; Artificial intelligence; Psychology; Classifier (UML); Natural language processing; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005256583,0.0002345326,0.0002572697,0.0007634432,0.0005610374,0.0005646254,0.0003206484,0.0002556194,0.001384501],"category_scores_gemma":[0.00232982,0.0002385942,0.000166207,0.0004652419,0.0007501256,0.0007514803,0.0006853646,0.0002623264,0.0002599737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005383734,"about_ca_system_score_gemma":0.0005145883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01143865,"about_ca_topic_score_gemma":0.01003747,"domain_scores_codex":[0.999773,0.00002852539,0.00002175862,0.00008427654,0.00006261922,0.00002981437],"domain_scores_gemma":[0.9986773,0.000538989,0.0003119029,0.000169858,0.0002173781,0.00008456995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007784171,0.00008238374,0.269848,0.0003805952,0.00005868646,0.005416755,0.05714695,0.0004839584,0.5636202,0.009245718,0.0008277866,0.09211064],"study_design_scores_gemma":[0.00002766245,0.0002435314,0.9171373,0.00003233115,0.00009211957,0.004213535,0.006463126,0.003194601,0.06077217,0.003053442,0.00466574,0.0001045256],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972475,0.00007564774,0.0006390099,0.00003172022,0.000003611961,0.00000622118,0.00006791917,0.00001840073,0.001909891],"genre_scores_gemma":[0.9985648,0.00004979041,0.0007203789,0.00001403466,0.000003237457,0.000006231322,0.0000926063,0.00001540546,0.000533525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01143865,"threshold_uncertainty_score":0.02274418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660543002118182,"score_gpt":0.2826780583544006,"score_spread":0.2660726283332188,"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."}}