{"id":"W7132436408","doi":"","title":"ᓄᑖᑦ ᓄᐊᑕᐅᓯᒪᔪᑦ ᑎᑎᕋᖅᑕᐅᓯᒪᔪᓂᑦ ᓄᓇᕗᒻᒥ ᒐᕙᒪᖓᑦᑕ ᐱᓕᕆᐊᖏᓐᓂᙶᖅᑐᑦ, ᐃᓄᒃᑎᑑᖅᑐᑦ ᖃᓪᓗᓈᑎᑑᓕᖅᓯᒪᔪᓂᒃ ᑲᑎᙵᓪᓗᑎᒃ - ᐊᒻᒪ ᖃᕋᓴᐅᔭᒃᑯᑦ ᑐᑭᓕᐅᖅᑕᐅᓯᒪᔪᑦ ᐃᓄᒃᑐᑦ ᖃᓪᓗᓈᑐᓪᓗ ᖃᓄᐃᒻᒪᖔᑕ ᓇᓗᓇᐃᖅᓯᔾᔪᑕᐅᓪᓗᓂ","year":2020,"lang":"en","type":"article","venue":"NPARC","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Indigenous language; Machine translation; Sentence; First language; Second language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0004193631,0.0004366723,0.0002788172,0.00117664,0.002723417,0.001248818,0.000471109,0.0002840217,0.0088581],"category_scores_gemma":[0.001775442,0.0002092513,0.0001689708,0.002375099,0.0008344472,0.0007474886,0.0007668863,0.0007557033,0.003195784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576982,"about_ca_system_score_gemma":0.002827058,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06694722,"about_ca_topic_score_gemma":0.1670651,"domain_scores_codex":[0.9994791,0.0001146619,0.00005447563,0.0001827928,0.0001068131,0.0000622136],"domain_scores_gemma":[0.9992224,0.0002064,0.00007110837,0.00008271087,0.0003624931,0.00005485907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001636876,0.0005996805,0.04241278,0.004036052,0.0001088796,0.002971995,0.02813791,0.003072013,0.1424857,0.02485293,0.1897602,0.559925],"study_design_scores_gemma":[0.00006909203,0.0002506351,0.1500374,0.0003579764,0.00009264662,0.001869568,0.01514528,0.007847326,0.05720508,0.002747678,0.7642681,0.0001091906],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7204922,0.003315441,0.03391099,0.001439642,0.001039473,0.00128277,0.09069844,0.002387308,0.1454338],"genre_scores_gemma":[0.7463228,0.001158678,0.06485623,0.0003293655,0.0001234798,0.001188647,0.141815,0.001049155,0.04315664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9330528,"threshold_uncertainty_score":0.1331151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0175971438060229,"score_gpt":0.2559683282143584,"score_spread":0.2383711844083355,"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."}}