{"id":"W2626887684","doi":"10.6000/1929-7092.2017.06.39","title":"Comparing Statistical and Data Mining Techniques for Enrichment Ontology with Instances","year":2017,"lang":"en","type":"article","venue":"Journal of Reviews on Global Economics","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ontology; Computer science; Data mining; Data science; Philosophy; Epistemology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001001731,0.00009452756,0.0004892634,0.00003097992,0.0001443045,0.000325527,0.001406094,0.00002401748,8.183929e-7],"category_scores_gemma":[0.0002288074,0.00006606386,0.0000344556,0.0000200039,0.00006373895,0.000662022,0.0002657524,0.00006361486,9.625661e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005494729,"about_ca_system_score_gemma":0.00006654474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001168386,"about_ca_topic_score_gemma":0.0001470441,"domain_scores_codex":[0.9991537,0.00003262899,0.0004230199,0.0002224468,0.00004489324,0.0001232526],"domain_scores_gemma":[0.9981378,0.00009330222,0.0009234227,0.0007264292,0.00003947069,0.00007963151],"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":[0.00005400895,0.0000483284,0.02742194,0.00005579311,0.0001079546,0.00001300745,0.00004300209,0.0000152756,0.00000111124,0.04303845,0.006405283,0.9227958],"study_design_scores_gemma":[0.001132019,0.00155462,0.01482797,0.001153728,0.0002505499,0.0004011817,0.00007370428,0.06650779,0.00002642773,0.003046347,0.91056,0.0004656565],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04330093,0.005790016,0.9458902,0.002130871,0.000283453,0.0002260735,0.0001297491,0.00001423646,0.002234469],"genre_scores_gemma":[0.1963981,0.007385459,0.7957867,0.0003000933,0.0001097123,0.000002965726,0.000006050116,0.000003299474,0.000007625928],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9223302,"threshold_uncertainty_score":0.3139064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1107370293395481,"score_gpt":0.3689221692097123,"score_spread":0.2581851398701642,"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."}}