{"id":"W3172907523","doi":"10.18653/v1/2021.naacl-main.251","title":"Negative language transfer in learner English: A new dataset","year":2021,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computational linguistics; Natural language processing; Artificial intelligence; Linguistics; English language; Cognitive science; Psychology; Philosophy","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":[0.001734291,0.0009125816,0.0009306481,0.00220391,0.001321211,0.001749235,0.001889024,0.002072856,0.006397553],"category_scores_gemma":[0.006540554,0.0002460198,0.000733805,0.001471293,0.000721184,0.002171016,0.003451484,0.001593183,0.01143916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005645805,"about_ca_system_score_gemma":0.001096963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007590585,"about_ca_topic_score_gemma":0.01516196,"domain_scores_codex":[0.9983562,0.0004487098,0.0001850037,0.0004043608,0.0003963416,0.0002095167],"domain_scores_gemma":[0.9960148,0.0009626308,0.0002262361,0.001019875,0.001153038,0.0006234324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002169266,0.002228623,0.07540006,0.001805858,0.0004535578,0.001692913,0.002209216,0.001765244,0.008866836,0.002354161,0.778711,0.1223432],"study_design_scores_gemma":[0.0009498411,0.001141912,0.2098844,0.0007311397,0.0003965505,0.004607376,0.007539479,0.0097255,0.01549716,0.005459714,0.7436766,0.0003903368],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3451017,0.002749874,0.005710467,0.00323814,0.001030529,0.0004358206,0.6192672,0.003240378,0.01922592],"genre_scores_gemma":[0.1329387,0.0004660526,0.005220984,0.0007635776,0.0002678953,0.000581288,0.8465649,0.0004767989,0.01271977],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007590585,"threshold_uncertainty_score":0.02140194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314132348300688,"score_gpt":0.2764317663861939,"score_spread":0.263290442903187,"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."}}