{"id":"W3150141661","doi":"10.5334/gjgl.1210","title":"How children attend to events before speaking: crosslinguistic evidence from the motion domain","year":2021,"lang":"en","type":"article","venue":"Glossa a journal of general linguistics","topic":"Categorization, perception, and language","field":"Psychology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Motion (physics); Psychology; Event (particle physics); Linguistics; Task (project management); Language production; Encoding (memory); Cognitive psychology; Computer science; Cognition; Artificial intelligence","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":[0.0005250958,0.0002252252,0.0003178946,0.00008183818,0.0002886197,0.0002276038,0.0004444587,0.0001333478,0.0005700364],"category_scores_gemma":[0.005583857,0.0001717621,0.0002069119,0.0003409129,0.00007082852,0.00004664971,0.00008237817,0.0003551959,0.00005758795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250579,"about_ca_system_score_gemma":0.0001532335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003965057,"about_ca_topic_score_gemma":0.0005783408,"domain_scores_codex":[0.9979756,0.0002697135,0.0005854609,0.0003165934,0.0005101899,0.000342442],"domain_scores_gemma":[0.9972032,0.0001590742,0.0004420944,0.0004847792,0.001510605,0.0002002722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004943835,0.0006606934,0.8610305,0.00003892235,0.0009792636,0.001349176,0.06914793,0.001130779,0.00587241,0.01468655,0.03149348,0.01311586],"study_design_scores_gemma":[0.001075156,0.0002590813,0.9611375,0.0002406005,0.0003092215,0.0004851501,0.001750971,0.00004524655,0.0002403127,0.006971499,0.02714109,0.0003441726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668758,0.001931415,0.02323904,0.001043549,0.006042877,0.0001634216,0.0001402769,0.00002104413,0.000542598],"genre_scores_gemma":[0.9725127,0.00005694214,0.006432435,0.0006573752,0.01844439,0.000002787534,0.0001007868,0.00003666335,0.001755963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.100107,"threshold_uncertainty_score":0.7004257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0240973930103329,"score_gpt":0.3147552563212715,"score_spread":0.2906578633109386,"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."}}