{"id":"W2914164063","doi":"10.1007/978-0-387-39940-9_3160","title":"Nonlinear Magnification","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Geophysics and Sensor Technology","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nonlinear system; Magnification; Computer science; Mathematics; Physics; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007545266,0.0003029418,0.0004737031,0.0001990151,0.00001960556,0.00001007361,0.0002644279,0.0003222925,0.00005792377],"category_scores_gemma":[0.00001053961,0.000321001,0.00009190795,0.00003961769,0.00004043594,0.00007037339,0.00003098982,0.0003396136,0.0003704084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003564278,"about_ca_system_score_gemma":0.00002155861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002725845,"about_ca_topic_score_gemma":0.000006439661,"domain_scores_codex":[0.9988051,0.00000623071,0.0005103091,0.0002602503,0.0002286855,0.0001893987],"domain_scores_gemma":[0.9988383,0.0000289192,0.0001535395,0.0008454553,0.00007544837,0.00005832232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002874593,0.0001914874,0.00003538653,0.007924682,0.0006970564,0.00030594,0.0002993978,0.003658908,0.006741692,0.677579,0.1658203,0.1367174],"study_design_scores_gemma":[0.0001236974,0.00004141039,0.000009060705,0.0002598558,0.00006078594,0.00001116368,0.00001019609,0.002550295,0.0001512771,0.0006153558,0.9958094,0.0003575542],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004000078,0.002698086,0.0003969879,0.00001620985,0.001126513,0.0004055821,0.00137512,0.0003866168,0.9931949],"genre_scores_gemma":[0.0129535,0.03161731,0.00381453,0.00002113674,0.002602022,0.0000505835,0.006512712,0.0004000146,0.9420282],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8299891,"threshold_uncertainty_score":0.9999242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009517698177829704,"score_gpt":0.1961071088083357,"score_spread":0.1865894106305059,"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."}}