{"id":"W4289774258","doi":"10.31227/osf.io/9srtx","title":"HUBUNGAN PENGUASAAN PIRANTI KOHESI DAN KOHERENSI DENGAN KEMAMPUAN MENGANALISIS WACANA","year":2018,"lang":"id","type":"preprint","venue":"","topic":"Educational Methods and Media Use","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Humanities; Physics; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001683167,0.0008179749,0.0006423726,0.001439833,0.00188672,0.004497803,0.0007070437,0.0007297812,0.03318194],"category_scores_gemma":[0.001826397,0.0005859251,0.0007324691,0.001515786,0.001065648,0.002392122,0.001787825,0.001425917,0.006073494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001339684,"about_ca_system_score_gemma":0.002609429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100048,"about_ca_topic_score_gemma":0.02345232,"domain_scores_codex":[0.9984971,0.0002441318,0.00008737529,0.0003374198,0.0006348476,0.0001990382],"domain_scores_gemma":[0.9978732,0.0004832108,0.0004353632,0.0002614807,0.0007448869,0.0002017878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001759573,0.0009778994,0.1792925,0.003478869,0.0004420443,0.001930408,0.01346509,0.001293192,0.2011444,0.01406091,0.01314629,0.5690088],"study_design_scores_gemma":[0.0000591842,0.001970075,0.3115869,0.001036104,0.0005961066,0.00262669,0.02484813,0.001641176,0.1894144,0.007656154,0.4583139,0.0002511428],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7206715,0.01035799,0.01927317,0.002934708,0.0004780413,0.0005478962,0.003519095,0.0005784761,0.2416391],"genre_scores_gemma":[0.805113,0.005559664,0.02148869,0.0006825099,0.00009245095,0.0002460266,0.001631911,0.0002207673,0.164965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03318194,"threshold_uncertainty_score":0.1110047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06497525330570898,"score_gpt":0.3370096444921746,"score_spread":0.2720343911864657,"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."}}