{"id":"W2593930809","doi":"10.5539/elt.v10n4p62","title":"Concept Map Technique as a New Method for Whole Text Translation","year":2017,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vocabulary; Paragraph; Significant difference; Mathematics education; Psychology; Equivalence (formal languages); Test (biology); Arabic; Natural language processing; Teaching method; Computer science; Artificial intelligence; Linguistics; Mathematics; Statistics","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":[0.001814162,0.0007658346,0.0005130635,0.002206573,0.0004242201,0.001294126,0.000829492,0.0004937798,0.008880974],"category_scores_gemma":[0.005109728,0.0002702425,0.0006805327,0.001882952,0.0008140781,0.001959796,0.001133583,0.000947419,0.002732646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002777342,"about_ca_system_score_gemma":0.000745007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002594859,"about_ca_topic_score_gemma":0.0002925101,"domain_scores_codex":[0.9973417,0.001315559,0.0001658077,0.0003260537,0.0007825712,0.00006825638],"domain_scores_gemma":[0.9973298,0.001797098,0.0001372153,0.0003105614,0.0003644627,0.00006076412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000244668,0.0002363565,0.0006066152,0.001101222,0.00007946208,0.000422973,0.002731078,0.001386763,0.03033386,0.01594172,0.005783369,0.9411319],"study_design_scores_gemma":[0.0006179136,0.003594556,0.01130348,0.001097096,0.0004510524,0.01128752,0.004350329,0.0767457,0.1470764,0.134125,0.6089453,0.0004056958],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01516929,0.001172865,0.9704757,0.0002589811,0.0004135226,0.0004753646,0.0001489329,0.001988291,0.009897038],"genre_scores_gemma":[0.0732144,0.000968036,0.9182676,0.00009981492,0.0001532962,0.0008258782,0.0002432279,0.0002943684,0.005933317],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008880974,"threshold_uncertainty_score":0.02970982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01628666816202498,"score_gpt":0.3455506392016345,"score_spread":0.3292639710396095,"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."}}