{"id":"W2110972852","doi":"10.1017/s1366728914000182","title":"Dynamic localization in second language English and German","year":2014,"lang":"en","type":"article","venue":"Bilingualism Language and Cognition","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Word order; Linguistics; Pitch accent; German; Computer science; Context (archaeology); Stress (linguistics); First language; Language transfer; Artificial intelligence; Speech recognition; History; Comprehension approach; Natural language; Prosody","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":[0.0005371683,0.0003382583,0.0002110671,0.0004556446,0.0003584028,0.001035433,0.0001349122,0.0002272532,0.002352714],"category_scores_gemma":[0.001288787,0.0001972463,0.0001007423,0.0002408738,0.0007273441,0.0008253676,0.0007484441,0.0002533213,0.0003168463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000652526,"about_ca_system_score_gemma":0.0003711953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006894008,"about_ca_topic_score_gemma":0.01455753,"domain_scores_codex":[0.9996818,0.00008804492,0.00002632661,0.0000795208,0.00006214852,0.0000621365],"domain_scores_gemma":[0.9994096,0.0002828751,0.0001121207,0.00004319569,0.00007852462,0.00007370742],"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":[0.002067461,0.0007744796,0.1999409,0.0008624665,0.0001150479,0.005052889,0.2598861,0.0005532642,0.4050593,0.02039924,0.002000648,0.1032882],"study_design_scores_gemma":[0.0002114003,0.001168816,0.8036245,0.0001064352,0.0001313554,0.005357841,0.1083847,0.00186516,0.04388552,0.003656187,0.03146554,0.0001425981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964728,0.0001450975,0.0002124671,0.00005096449,0.000004175281,0.000004794179,0.00003173251,0.000005715756,0.003072241],"genre_scores_gemma":[0.9991308,0.00005127749,0.0001222546,0.00002299734,0.000001037766,0.000003014976,0.00003064855,0.000003340977,0.0006345539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006894008,"threshold_uncertainty_score":0.01370782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007075374373844603,"score_gpt":0.2834456426787183,"score_spread":0.2763702683048737,"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."}}