{"id":"W4391689861","doi":"10.1016/j.softx.2024.101649","title":"APRCOIE: An open information extraction system for Chinese","year":2024,"lang":"en","type":"article","venue":"SoftwareX","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Office for Philosophy and Social Sciences","keywords":"Computer science; Information extraction; Information retrieval; World Wide Web; Natural language processing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00154578,0.001335955,0.0007205856,0.006341181,0.001015526,0.001426942,0.001181519,0.0005900644,0.01298176],"category_scores_gemma":[0.006052715,0.0005374884,0.0009155854,0.005193857,0.0004488428,0.004146472,0.001946201,0.0008096386,0.007840032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009039695,"about_ca_system_score_gemma":0.004484804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009312331,"about_ca_topic_score_gemma":0.01138166,"domain_scores_codex":[0.9991212,0.0001178331,0.0001555184,0.0002147755,0.0003266885,0.00006393691],"domain_scores_gemma":[0.9973984,0.0008932847,0.0002869726,0.000396991,0.0008833505,0.0001410529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005054593,0.0001722564,0.009173991,0.002571608,0.0002178776,0.001604179,0.002110609,0.003327398,0.02298608,0.0249467,0.377106,0.5552778],"study_design_scores_gemma":[0.0002008949,0.0001639419,0.01496372,0.0002821764,0.0002583117,0.001286597,0.000664182,0.07772893,0.04733358,0.02173332,0.8351061,0.0002781033],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0319692,0.001533307,0.5403139,0.001379478,0.0004355156,0.002178808,0.1376347,0.2460559,0.03849907],"genre_scores_gemma":[0.1132347,0.00174342,0.5810025,0.0004698942,0.0002907623,0.002140137,0.2668677,0.007082346,0.02716845],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01298176,"threshold_uncertainty_score":0.04342836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02400441237466808,"score_gpt":0.314194521563081,"score_spread":0.2901901091884129,"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."}}