{"id":"W28660552","doi":"10.1007/s11886-017-0876-4","title":"A community reference grammar of Labrador Inuttitut","year":2009,"lang":"en","type":"article","venue":"Current Cardiology Reports","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grammar; Computer science; Linguistics; Rule-based machine translation; Speech community; Artificial intelligence; Natural language processing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001559627,0.001125348,0.001115426,0.004374703,0.002542051,0.005883009,0.001656728,0.001978551,0.3183237],"category_scores_gemma":[0.01080039,0.0004001286,0.0003699569,0.007839275,0.001199918,0.004364481,0.002291676,0.002352604,0.2095585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002523638,"about_ca_system_score_gemma":0.002778632,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01591474,"about_ca_topic_score_gemma":0.01487504,"domain_scores_codex":[0.9980922,0.0006148812,0.0002628755,0.0003421498,0.0005210579,0.000166914],"domain_scores_gemma":[0.9940425,0.001836869,0.0004332396,0.0009315535,0.002451688,0.0003041024],"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":[0.00006164928,0.00002260499,0.0002681523,0.0001924369,0.000003489896,0.0001364191,0.0005636098,0.000125587,0.0002861185,0.07228967,0.8711066,0.05494371],"study_design_scores_gemma":[0.000002188935,0.000002372884,0.0001021752,0.0000624544,7.899645e-7,0.00004527183,0.00006933229,0.00007576076,0.00005467798,0.001363683,0.9982176,0.000003536872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001922331,0.005440918,0.01343756,0.0171601,0.01514629,0.0002126156,0.02210609,0.002880383,0.9216937],"genre_scores_gemma":[0.04461462,0.0075328,0.01546473,0.006852053,0.006188956,0.0004138962,0.03932586,0.006408835,0.8731983],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9840853,"threshold_uncertainty_score":0.9723285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03529709228215173,"score_gpt":0.3175967167334501,"score_spread":0.2822996244512984,"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."}}