{"id":"W1961366917","doi":"10.3968/j.ans.1715787020100301.003","title":"Analysis and Application of Extension Correlation and Correspondence under Uncertainty","year":2010,"lang":"en","type":"article","venue":"Advances in natural science/Advances in natural sciences","topic":"Extenics and Innovation Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extension (predicate logic); Interval (graph theory); Data mining; Reliability (semiconductor); Mathematics; Correlation; Function (biology); Relation (database); Set (abstract data type); Group (periodic table); Computer science; Statistics","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":[0.00909513,0.0007889678,0.001168254,0.003107473,0.001407084,0.002858535,0.001232267,0.001149478,0.002277873],"category_scores_gemma":[0.0510577,0.0004352999,0.001374628,0.003833202,0.00315429,0.007038633,0.0029542,0.001694405,0.0002039099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002123094,"about_ca_system_score_gemma":0.00195809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00143639,"about_ca_topic_score_gemma":0.0005319369,"domain_scores_codex":[0.9906916,0.004293564,0.0004964211,0.001347928,0.002794344,0.0003761587],"domain_scores_gemma":[0.9689441,0.02260553,0.002688462,0.002483369,0.002870969,0.0004076981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002146448,0.00007004702,0.01387053,0.000217508,0.0001669055,0.0003548495,0.0009189777,0.2195468,0.001189406,0.645804,0.0007693933,0.116877],"study_design_scores_gemma":[0.0000205852,0.0001197785,0.004478378,0.00008208679,0.00007633496,0.0002716886,0.0003192901,0.5823931,0.002267228,0.4074708,0.002432784,0.00006797697],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07565298,0.000372377,0.916696,0.0003814888,0.00003778468,0.00005489969,0.00009470783,0.00008981641,0.006619913],"genre_scores_gemma":[0.9122729,0.0004486973,0.08577127,0.00006553688,0.00008564649,0.000134701,0.0001038347,0.00003035145,0.001087039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00909513,"threshold_uncertainty_score":0.04810023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005843331193759251,"score_gpt":0.3184618683365577,"score_spread":0.3126185371427984,"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."}}