{"id":"W3215500461","doi":"10.5281/zenodo.2553357","title":"The dative dataset of World Englishes","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Linguistics, Language Diversity, and Identity","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dative case; World Englishes; Linguistics; Computer science; Natural language processing; History; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006877433,0.0001707233,0.0001955081,0.000211268,0.003765732,0.001633318,0.001983176,0.0000497871,0.042718],"category_scores_gemma":[0.008533221,0.0001382555,0.00006092331,0.0001175887,0.001047137,0.00019452,0.002122928,0.0003174035,0.006325841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006539265,"about_ca_system_score_gemma":0.000005491503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006740057,"about_ca_topic_score_gemma":0.0002500781,"domain_scores_codex":[0.9984736,0.0002771179,0.000301206,0.0003203617,0.0003570191,0.0002706292],"domain_scores_gemma":[0.9956661,0.00007372935,0.0002928989,0.0007954743,0.003098277,0.00007348706],"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":[0.0000328306,0.00007351092,1.840633e-7,0.00009740829,0.00009638074,0.000006027301,0.003492941,1.715719e-7,3.399425e-7,0.001838675,0.9937413,0.0006202674],"study_design_scores_gemma":[0.0001600196,0.00009506625,0.000002896717,0.00003886618,0.00006903365,7.218457e-7,0.002641973,0.000002732932,0.00000926376,0.0001687958,0.9966531,0.0001575546],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003318382,0.0000898494,0.000004256046,0.00002812284,0.002597193,0.0002210277,0.9811634,0.00009813951,0.01576479],"genre_scores_gemma":[0.0001470592,0.0001784531,0.000007667508,0.000113592,0.006169918,1.554967e-8,0.9909543,0.0003091295,0.002119825],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03639216,"threshold_uncertainty_score":0.9998183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05134361865399407,"score_gpt":0.2505987741797388,"score_spread":0.1992551555257447,"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."}}