{"id":"W3180605385","doi":"","title":"Which Would You Rather Choose, Lingua Franca or Machine Translation?: Two Case Studies","year":2021,"lang":"en","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lingua franca; Linguistics; Computer science; Translation (biology); Artificial intelligence; Philosophy; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006861318,0.0006226847,0.0004906742,0.001105309,0.009486466,0.003800361,0.001372226,0.005522895,0.005068814],"category_scores_gemma":[0.01403941,0.0004461493,0.0004759042,0.002467824,0.003515275,0.003964941,0.002772144,0.002670513,0.0008749044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004082752,"about_ca_system_score_gemma":0.002392094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0299785,"about_ca_topic_score_gemma":0.0602161,"domain_scores_codex":[0.9938594,0.004199821,0.0002353383,0.0002860927,0.0006517114,0.000767714],"domain_scores_gemma":[0.9922259,0.005747243,0.0005351347,0.0002030292,0.0006605713,0.0006281828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005199114,0.001664014,0.03050438,0.00106859,0.00004517566,0.1378573,0.6831315,0.0009039855,0.00199831,0.03364549,0.03457653,0.07408497],"study_design_scores_gemma":[0.00005380283,0.0001864655,0.008531272,0.0009023543,0.00003607298,0.02858341,0.8330716,0.000712612,0.001719429,0.004011455,0.1221064,0.00008518095],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9210369,0.002805694,0.004423498,0.02250462,0.0002219668,0.0006346147,0.0003327515,0.00002137203,0.04801852],"genre_scores_gemma":[0.9655055,0.003114044,0.006869555,0.004495771,0.00006421888,0.0004535889,0.0001755328,0.00004429069,0.01927748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0299785,"threshold_uncertainty_score":0.05960804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08509964623023353,"score_gpt":0.338768304272267,"score_spread":0.2536686580420334,"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."}}