{"id":"W4327564645","doi":"","title":"First steps into a Community Interpreting training model in Quebec","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Computer science; Geography","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":[0.006441028,0.0004084595,0.0003657689,0.0008539268,0.008538863,0.005978437,0.00298453,0.001934373,0.01777917],"category_scores_gemma":[0.01063148,0.0003312442,0.0003924381,0.001315392,0.001920625,0.002943693,0.002277873,0.002034737,0.001333492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06403367,"about_ca_system_score_gemma":0.1346902,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.972599,"about_ca_topic_score_gemma":0.9876352,"domain_scores_codex":[0.9959187,0.002178704,0.00008353476,0.0003542121,0.0004726851,0.0009921452],"domain_scores_gemma":[0.9894915,0.001579993,0.0002410913,0.0005037954,0.005010334,0.00317332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009017003,0.00321657,0.2086811,0.0004869261,0.000139649,0.001625843,0.05617573,0.04231044,0.004576043,0.1631637,0.1443803,0.374342],"study_design_scores_gemma":[0.0004944394,0.001416683,0.2327321,0.002006443,0.0002221577,0.0006046184,0.16897,0.1682056,0.00391769,0.03372597,0.387268,0.0004362256],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6212708,0.000987537,0.03650142,0.1011746,0.0004017854,0.001870909,0.002219322,0.001215262,0.2343583],"genre_scores_gemma":[0.9284589,0.0003264608,0.02757691,0.002672885,0.00002865441,0.0003408507,0.0005749369,0.0001053769,0.03991508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06403367,"threshold_uncertainty_score":0.464599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06768956691797473,"score_gpt":0.3642952083357465,"score_spread":0.2966056414177718,"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."}}