{"id":"W1964518358","doi":"10.5539/elt.v4n1p209","title":"Abbreviations in Maritime English","year":2011,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Reading (process); Psychology; Natural language processing; Mathematics education; Artificial intelligence; Computer science; Philosophy","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":[0.0007478295,0.0003636976,0.0002288691,0.001875694,0.002200753,0.003042829,0.0004604413,0.0006532889,0.009240382],"category_scores_gemma":[0.004979703,0.0001778306,0.0002119666,0.00352576,0.00366062,0.00512135,0.001589087,0.000975474,0.001585001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001199306,"about_ca_system_score_gemma":0.00111786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004058711,"about_ca_topic_score_gemma":0.004009465,"domain_scores_codex":[0.9982446,0.0008746136,0.0001898513,0.0002422545,0.0003192957,0.0001294058],"domain_scores_gemma":[0.9980337,0.0007354555,0.0003820583,0.0002876573,0.0004835391,0.00007758378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005552635,0.00001129686,0.001953107,0.0002790019,0.00000828329,0.0006617099,0.0329584,0.0002009322,0.004871378,0.8941178,0.004274047,0.06060859],"study_design_scores_gemma":[0.00001384295,0.00007610655,0.0103692,0.0003997019,0.00003979259,0.00201037,0.03555668,0.002124424,0.006329814,0.2322915,0.7106982,0.00009045121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.274803,0.01447999,0.1249281,0.006199777,0.002609134,0.0001484594,0.0007323133,0.001180086,0.5749191],"genre_scores_gemma":[0.962535,0.001961513,0.01838903,0.000297512,0.0002586454,0.00003793028,0.0001865026,0.0001597554,0.01617411],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.009240382,"threshold_uncertainty_score":0.03091216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02147099339863939,"score_gpt":0.2225578308315084,"score_spread":0.201086837432869,"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."}}