{"id":"W4235608485","doi":"10.15242/icehm.ed1116065","title":"Technical Approach for Second Language Acquisition (SLA) Testing Using Multimodal Environments","year":2016,"lang":"en","type":"article","venue":"","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education, British Columbia; Ministerio de Educación, Cultura y Deporte; University College London","keywords":"Computer science; Natural language processing; Programming language; Human–computer interaction","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001591318,0.00006917759,0.00006329931,0.00004710179,0.00009291688,0.00001896627,0.0003059984,0.00007069301,0.00003467108],"category_scores_gemma":[0.00003114465,0.00004785338,0.00002526588,0.00008049379,0.0000411788,0.0002375015,0.0001202551,0.00004252446,0.000008480644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006945334,"about_ca_system_score_gemma":0.00002904849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002031985,"about_ca_topic_score_gemma":4.438267e-7,"domain_scores_codex":[0.9993743,0.00001296634,0.0001077904,0.0002559924,0.00008877717,0.0001601203],"domain_scores_gemma":[0.9995379,0.0001380827,0.00004508698,0.0002371776,0.00001161454,0.00003014808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002585216,0.0002261953,0.002833075,0.000009540035,0.000009082669,0.000001240786,0.00005734884,0.00003131113,0.9066468,0.05009551,0.0002117924,0.03987551],"study_design_scores_gemma":[0.003122567,0.0004451163,0.060649,0.0001096299,0.00003233929,0.0002139315,0.0005029972,0.353088,0.5489684,0.02983511,0.001852068,0.001180813],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06925336,0.00001108942,0.9285069,0.0003896292,0.00004945291,0.0001593904,0.000003351579,0.0001163773,0.001510506],"genre_scores_gemma":[0.5107844,1.154969e-7,0.488732,0.00006878287,0.0000260552,0.00002626598,0.000001570069,0.0000026123,0.0003581545],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4415311,"threshold_uncertainty_score":0.1951404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0331391226241247,"score_gpt":0.3039812758208288,"score_spread":0.2708421531967041,"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."}}