{"id":"W4387656947","doi":"10.56040/unkb1524","title":"Teaching Hindi and Urdu as Hindi-Urdu","year":2018,"lang":"en","type":"article","venue":"Electronic Journal of Foreign Language Teaching","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Urdu; Hindi; Linguistics; Natural language processing; Artificial intelligence; Computer science; 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":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003396288,0.0003387462,0.0004708601,0.0004176728,0.001329718,0.0004342838,0.0004537158,0.0001000334,0.001733954],"category_scores_gemma":[0.0005683948,0.0002700611,0.0002158388,0.00003521374,0.0002378305,0.0007737423,0.00008757491,0.003218494,0.00006218052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002024444,"about_ca_system_score_gemma":0.0001771166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002130703,"about_ca_topic_score_gemma":0.000719607,"domain_scores_codex":[0.9972149,0.0004880406,0.000614124,0.0002997669,0.0004396562,0.0009435259],"domain_scores_gemma":[0.9985864,0.0002655231,0.000606368,0.0002774268,0.00008125368,0.0001830751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008507638,0.00008649446,0.0002893202,0.00003100513,0.0002646238,0.0001460455,0.3307639,0.00000292072,0.001534003,0.5062879,0.0006246471,0.1598841],"study_design_scores_gemma":[0.005168323,0.006986481,0.0002160037,0.0009618437,0.0006853042,0.006779376,0.5220726,0.0007918584,0.001538845,0.04671986,0.4060631,0.002016432],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8465902,0.004916109,0.0006014967,0.0002864116,0.000310021,0.0001019571,0.000003704299,0.0001069307,0.1470832],"genre_scores_gemma":[0.985361,0.00002113523,0.0004409119,0.0008949601,0.00470167,0.000002064357,0.000008797367,0.00007261591,0.008496776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4595681,"threshold_uncertainty_score":0.9999751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007371749913824552,"score_gpt":0.245977051717896,"score_spread":0.2386053018040714,"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."}}