{"id":"W1786535492","doi":"10.14778/2824032.2824111","title":"Gain control over your integration evaluations","year":2015,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Data integration; Generality; Scalability; Information integration; Schema (genetic algorithms); System integration; Metadata; Reuse; Schema evolution; Data mining; Information retrieval; Database schema; Database; World Wide Web; Database design","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":[0.0005808339,0.00008706969,0.0001198538,0.00005241963,0.00005839474,0.0000815086,0.0007167887,0.0000306594,0.000004536143],"category_scores_gemma":[0.0003997622,0.00005309679,0.00006184859,0.0002003241,0.00004081205,0.0003243946,0.0001674372,0.00006965561,0.00001105069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000718287,"about_ca_system_score_gemma":0.00005628224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005459421,"about_ca_topic_score_gemma":0.000004575882,"domain_scores_codex":[0.9990633,0.0000104798,0.0001909827,0.0001675004,0.0004210822,0.0001466591],"domain_scores_gemma":[0.9993159,0.00003363751,0.0001553741,0.0001471174,0.0003004488,0.00004749608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005300509,0.0003158306,0.02145125,0.00003813534,0.0001085533,6.662124e-7,0.009570962,0.0002992713,0.07572036,0.809132,0.04399035,0.03931966],"study_design_scores_gemma":[0.005865416,0.0006125956,0.05930647,0.0002034802,0.0001596111,0.00003947758,0.003830597,0.2114753,0.410964,0.3014613,0.005483503,0.0005981512],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6659503,0.0009263266,0.2261869,0.03794499,0.002820707,0.002394375,0.000008661082,0.0005264358,0.06324127],"genre_scores_gemma":[0.993252,0.00000467191,0.006045384,0.0003647877,0.0000456779,0.00003831959,2.094412e-7,0.000003429088,0.0002454644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5076706,"threshold_uncertainty_score":0.2165224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05622812223294921,"score_gpt":0.3080118234033961,"score_spread":0.2517837011704468,"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."}}