{"id":"W4250677783","doi":"10.31234/osf.io/298cz","title":"Effects of language mixing on bilingual children’s word learning","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Language Development and Disorders","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; Concordia University; Fondation Pour l'Audition","keywords":"Sentence; Linguistics; Word (group theory); Language transfer; Mixing (physics); First language; Psychology; Neuroscience of multilingualism; Computer science; Comprehension approach; Natural language processing; Natural language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001269513,0.000856835,0.0004617427,0.0005735548,0.0005631432,0.000711106,0.0002650554,0.0004137253,0.001953382],"category_scores_gemma":[0.002731577,0.0003640432,0.0003066357,0.0001520384,0.001040942,0.0006689238,0.001227254,0.0007338068,0.0002012145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004755171,"about_ca_system_score_gemma":0.0007130291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002772828,"about_ca_topic_score_gemma":0.004279101,"domain_scores_codex":[0.9986721,0.0003093073,0.0001302183,0.0003506386,0.000315509,0.000222273],"domain_scores_gemma":[0.9974219,0.001043411,0.0006206752,0.0002129597,0.0001974569,0.0005035855],"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":[0.005657361,0.002099375,0.1408009,0.0003056241,0.0001225464,0.002333896,0.01055521,0.0002155841,0.8053626,0.0006309748,0.0001878999,0.03172801],"study_design_scores_gemma":[0.000327333,0.007810835,0.822859,0.00007393221,0.0002064148,0.002667417,0.005081575,0.0007356835,0.1574719,0.000986021,0.001704084,0.00007573103],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992347,0.00005633412,0.00009597866,0.0000143238,0.000002150354,0.000006217843,0.00001357176,0.000006406218,0.0005702999],"genre_scores_gemma":[0.9988658,0.00007106211,0.0005728363,0.00002385177,0.000002466505,0.00002680443,0.00004251284,0.000009345657,0.0003852155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002772828,"threshold_uncertainty_score":0.006713927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01052927253399021,"score_gpt":0.2909745113617621,"score_spread":0.2804452388277718,"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."}}