{"id":"W2153305265","doi":"10.1504/ijbpim.2013.059136","title":"RSenter: terms mining tool from unstructured data sources","year":2013,"lang":"en","type":"article","venue":"International Journal of Business Process Integration and Management","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Unstructured data; Computer science; Data mining; Data science; Big data","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001890933,0.0001430174,0.0001555337,0.0002931863,0.00005332408,0.0009112405,0.002128854,0.00004431766,0.00004263676],"category_scores_gemma":[0.0001022442,0.0001031118,0.00002674251,0.0002023995,0.0000428065,0.002936915,0.000551761,0.0001242337,0.000003543051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003610071,"about_ca_system_score_gemma":0.0000302424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004478296,"about_ca_topic_score_gemma":0.000009726273,"domain_scores_codex":[0.9986122,0.00002295127,0.000436526,0.0002628156,0.0005557826,0.0001097004],"domain_scores_gemma":[0.9983079,0.00003367969,0.0004526142,0.0002850346,0.0008778636,0.0000429113],"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":[0.00002970963,0.00006740737,0.0009191679,0.00004775923,0.0001898512,0.00007507196,0.0009694471,0.00002868282,0.00115284,0.009770103,0.002960183,0.9837898],"study_design_scores_gemma":[0.006572954,0.0002879986,0.0739473,0.005711564,0.0003348463,0.00140499,0.005114967,0.1967648,0.04649967,0.632295,0.02862194,0.002443891],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05289073,0.0007254268,0.9400695,0.004824138,0.0009569461,0.0001604767,0.000007757382,0.00008823826,0.0002768011],"genre_scores_gemma":[0.7569249,0.0002208321,0.2418425,0.0006887309,0.0001953703,0.000008070158,0.00003070372,0.000007401326,0.00008149132],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9813459,"threshold_uncertainty_score":0.8787113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636727443417805,"score_gpt":0.2825990706188246,"score_spread":0.2662317961846465,"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."}}