{"id":"W4281854421","doi":"10.5539/ijel.v12n4p25","title":"The Impact of Language in Rescue and Security Field","year":2022,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fire fighter; Face (sociological concept); Competence (human resources); Sentence; English language; Work (physics); Arabic; Psychology; Medical education; Computer security; Public relations; Business; Political science; Engineering; Sociology; Computer science; Mathematics education; Social psychology; Linguistics; Medicine; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001412196,0.00031623,0.0002447783,0.0007813232,0.002067062,0.002528191,0.0006462131,0.0004378364,0.009844561],"category_scores_gemma":[0.007872378,0.0001604217,0.0002991685,0.0007554398,0.002332103,0.001472462,0.002239253,0.001053834,0.0009647203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002229743,"about_ca_system_score_gemma":0.003236912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02676026,"about_ca_topic_score_gemma":0.03549662,"domain_scores_codex":[0.9969183,0.001342491,0.0001534812,0.0002506352,0.0006576533,0.0006774848],"domain_scores_gemma":[0.9936429,0.002184389,0.00166987,0.0001522205,0.0009969744,0.001353576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003413854,0.0006222225,0.8300748,0.0004380789,0.00009345793,0.004299865,0.1049695,0.0002147587,0.002479774,0.003473498,0.003328464,0.04966412],"study_design_scores_gemma":[0.00001029281,0.000257389,0.7902486,0.0003016283,0.00005079448,0.001064369,0.1974979,0.0001815268,0.0004147439,0.0004580559,0.0094812,0.0000334299],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840718,0.0004450961,0.00009271461,0.0009532125,0.00003915397,0.00001051175,0.00005109475,0.000004745428,0.01433155],"genre_scores_gemma":[0.9972001,0.0002373479,0.00007100209,0.0001669561,0.00001463644,0.000007409285,0.00002729861,0.000005449745,0.002269752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02676026,"threshold_uncertainty_score":0.05320895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02869924133904325,"score_gpt":0.4508485245386196,"score_spread":0.4221492831995763,"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."}}