{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000197237,0.0001212506,0.0001638806,0.0002604181,0.00008601269,0.00003211323,0.0000648787,0.00007438015,0.0001697324],"category_scores_gemma":[0.0000401451,0.0001066036,0.00002470175,0.0002277636,0.00006025363,0.0002298476,0.0000171422,0.0001464243,0.00008632414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002269567,"about_ca_system_score_gemma":0.0000593518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001333504,"about_ca_topic_score_gemma":0.0000212007,"domain_scores_codex":[0.9991146,0.00006407276,0.0003626328,0.0001307873,0.0001943835,0.0001335141],"domain_scores_gemma":[0.9995406,0.00005129043,0.0002006457,0.00009686557,0.00007123532,0.00003941801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001897188,0.0001512794,0.1919078,0.00007073295,0.00004008496,0.000009078703,0.4701254,0.0003776884,0.0001308824,0.01427266,0.0005982165,0.3221264],"study_design_scores_gemma":[0.001001823,0.0001057064,0.9582155,0.00005353783,0.000004273286,0.00002744409,0.03618445,0.003425746,0.0000381769,0.0001618663,0.0006248174,0.0001566157],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9070742,0.00005316364,0.007417061,0.0001140034,0.00008875622,0.0001759325,0.000007645526,0.00004565277,0.08502363],"genre_scores_gemma":[0.9987278,0.0000138975,0.0003965639,0.00006332622,0.00002652753,0.00001469577,0.0002081888,0.000005601403,0.0005434292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7663078,"threshold_uncertainty_score":0.4347169,"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."}}