{"id":"W2885392053","doi":"10.5539/cis.v11n3p89","title":"Design and Implementation of China HowNet Knowledge Map Generation Module Literature","year":2018,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Field (mathematics); Visualization; Information retrieval; Enlightenment; Knowledge extraction; Data science; Data mining","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":[0.001393367,0.0007337239,0.0005794212,0.007325094,0.001496963,0.002968061,0.001343026,0.0005948793,0.01887747],"category_scores_gemma":[0.004783047,0.0004487598,0.000846583,0.004593949,0.0005250786,0.003334245,0.002208898,0.0006087637,0.004605015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001405708,"about_ca_system_score_gemma":0.004079788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01265841,"about_ca_topic_score_gemma":0.009012184,"domain_scores_codex":[0.998561,0.0002018145,0.0001836228,0.0005086631,0.0004390549,0.0001058586],"domain_scores_gemma":[0.998001,0.0003511629,0.0001494253,0.0003519613,0.000984177,0.0001622779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002846144,0.0003347657,0.008005152,0.001450357,0.0001565875,0.0005347194,0.003955141,0.007151561,0.01239739,0.04662063,0.07865873,0.8404504],"study_design_scores_gemma":[0.0001681677,0.0001974012,0.01402421,0.000550497,0.0003344356,0.0006444358,0.004260419,0.1722743,0.04746652,0.04058276,0.7193101,0.0001867441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03356517,0.0003757444,0.8387007,0.00114221,0.000321076,0.002232972,0.01155611,0.0541946,0.05791142],"genre_scores_gemma":[0.183935,0.0005479314,0.7339329,0.0004826353,0.000112568,0.003767241,0.03561793,0.002485323,0.03911844],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01887747,"threshold_uncertainty_score":0.06315148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01774687199799569,"score_gpt":0.3135935213555093,"score_spread":0.2958466493575136,"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."}}